http://www.peterbeerli.com/classes/api.php?action=feedcontributions&user=Peter+Beerli&feedformat=atomPeter Beerli's Classes - User contributions [en]2024-03-29T10:15:25ZUser contributionsMediaWiki 1.34.0http://www.peterbeerli.com/classes/index.php?title=ISC-4304&diff=1045ISC-43042018-01-13T15:16:57Z<p>Peter Beerli: /* Programming for Science Applications */</p>
<hr />
<div>== Programming for Science Applications==<br />
<div>[[File:eniac4.jpg|left|top]]<br />
(Gloria Ruth Gordon [Bolotsky] and Ester Gerston programming the ENIAC:[http://www.columbia.edu/cu/computinghistory/eniac.html History of ENIAC])</div><br />
<div style="clear: both"></div><br />
This course provides knowledge of a scripting language (python) that serves as a front-end to popular packages and frameworks, along with a compiled language (C++). Students will study and practice object-oriented scientific programming with the scripting and compiled language. In the laboratory component of the course, students will apply the concepts learned in several scientific applications.<br />
<br />
* [[Media:Syllabus-ISC4304-S2018.pdf | Syllabus]]<br />
* [[Notes ISC-4304 | Class notes and slides]]<br />
* [[Homework for ISC-4304 | Homework ]]<br />
* [[Lab assignments for ISC-4304 | Lab assignments]]<br />
* [[Resources for ISC-4304 | Resources]]<br />
* [[FunExamples | Fun examples we will run in class]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Homework_for_ISC-4304&diff=1044Homework for ISC-43042018-01-13T15:07:35Z<p>Peter Beerli: /* Old homework from prefious years */</p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2017.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
<br />
== Homework for Spring 2018 ==<br />
*[[Media:isc4304homework1S2018.pdf| Home work 1 due January 18, 2017]] <br />
<br />
<br><br />
== Old homework from previous years ==<br />
*[[Media:isc4304homework1S2017.pdf| Home work 1]] <br />
*[[Media:isc4304homework2S2017.pdf| Home work 2]] <br />
*[[Media:isc4304homework3S2017.pdf| Home work 3]] (use this worksheet to turn on the homework [http://peterbeerli.com/classdata/ISC4304/codes/homework3S2017worksheet.txt homework3worksheet.txt])<br />
*[[Media:isc4304homework1.pdf| Home work 1]] <br />
*[[Media:isc4304homework2.pdf| Home work 2]] <br />
*[[Media:isc4304homework3.pdf| Home work 3]] <br />
*[[Media:isc4304homework4.pdf| Home work 4]]<br />
*[[Media:isc4304homework5.pdf| Home work 5]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=File:Isc4304homework1S2018.pdf&diff=1043File:Isc4304homework1S2018.pdf2018-01-12T14:31:56Z<p>Peter Beerli: </p>
<hr />
<div></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Homework_for_ISC-4304&diff=1042Homework for ISC-43042018-01-12T14:31:29Z<p>Peter Beerli: </p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2017.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
<br />
== Homework for Spring 2018 ==<br />
*[[Media:isc4304homework1S2018.pdf| Home work 1 due January 18, 2017]] <br />
<br />
<br><br />
== Old homework from prefious years ==<br />
*[[Media:isc4304homework1S2017.pdf| Home work 1]] <br />
*[[Media:isc4304homework2S2017.pdf| Home work 2]] <br />
*[[Media:isc4304homework3S2017.pdf| Home work 3]] (use this worksheet to turn on the homework [http://peterbeerli.com/classdata/ISC4304/codes/homework3S2017worksheet.txt homework3worksheet.txt])<br />
*[[Media:isc4304homework1.pdf| Home work 1]] <br />
*[[Media:isc4304homework2.pdf| Home work 2]] <br />
*[[Media:isc4304homework3.pdf| Home work 3]] <br />
*[[Media:isc4304homework4.pdf| Home work 4]]<br />
*[[Media:isc4304homework5.pdf| Home work 5]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=File:Isc4304firstpythonS2018.pdf&diff=1041File:Isc4304firstpythonS2018.pdf2018-01-10T14:37:33Z<p>Peter Beerli: </p>
<hr />
<div></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Notes_ISC-4304&diff=1040Notes ISC-43042018-01-10T14:36:58Z<p>Peter Beerli: </p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2018.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
<br />
[[file:peterteaching.jpg | 300px | top | right ]]<br />
<br><br />
(for Spring semester 2018)<br />
*[[Media:isc4304overview1S2018.pdf| Lecture 1 (Syllabus/Introduction) January 8]]<br />
*[[Media:isc4304firstpythonS2018.pdf| Lecture 2 (Python baby steps) January 10]]<br />
<br />
----<br />
<br />
<br><br />
(OLD SLIDES for Spring semester 2017)<br />
*[[Media:isc4304overview1S2017.pdf| Lecture 1 (Overview) January 10]]<br />
*[[Media:isc4304modules2S2017.pdf| Lecture 2 (Python Modules and Interaction with the OS) January 12]]<br />
*[[Media:isc4304containers3S2017.pdf| Lecture 3 (Containers in python) January 17]]<br />
*[[Media:isc4304functions4S2017.pdf| Lecture 4 (Functions) January 29]]<br />
*[[Media:isc4304textprocessing+mix5S2017.pdf| Lecture 5 (Text processing) January 24]]<br />
*[[Media:isc4304matplotlib6S2017.pdf| Lecture 6 (Plotting with matplotlib) January 26]]<br />
*[[Media:isc4304numpy7S2017.pdf| Lecture 7 (scientific computing with numpy) January 31]]<br />
*[[Media:isc4304scipy8S2017.pdf| Lecture 8 (scientific computing with scipy) February 2]]<br />
*[[Media:isc4304classes9S2017.pdf| Lecture 9 (Object orientation with Python 1) February 7]]<br />
*[[Media:isc4304classes10S2017.pdf| Lecture 10 (Object orientation with Python 2) February 9]]<br />
* Tuesday February 14 2017: Question answer session on matplotlib<br />
*[[Media:isc4304iterators12S2017.pdf| Lecture 12 (Iterators and Generators) February 16]]<br />
*[[Media:isc4304debug.pdf| Lecture 13 (Debugging and Beautifcation) February 23]]<br />
*[[Media:isc4304speedS2017.pdf| Lecture 14 (Speed) February 28]] ([[Media:EuroTutorial2011.pdf| Original Lecture]])<br />
*[[Media:isc4304julia.pdf| Lecture 15 (alternatives to Python: Julia) March 2]] (Complete [http://people.sc.fsu.edu/~pbeerli/downloads/classes/Julia-EuroSciPy14-mod.zip package] with IJulia notebooks) [for installation of Julia and IJulia look at [http://www.julialang.org the Julia main website] ].<br />
*[[Media:isc4304cplusplusintro.pdf| Lecture 16 C++ Pointers and such March 21]]<br />
*[[Media:isc4304cplusplusreferences.pdf| Lecture 17 C++ References March 23]]<br />
*[[Media:isc4304STL.pdf| Lecture 18 STL March 28]]<br />
*Additional Material on const correctness and operator overloading [http://courses.cms.caltech.edu/cs11/material/cpp/donnie/cpp-ops.html operator instructions]; [https://isocpp.org/wiki/faq/const-correctness Const-correctness]<br />
* [[Media:isc4304boost_python1S2017.pdf| Lecture 19 Boost-Python March 30]] Installation of Boost-Python from scratch and trial of a simple example C++/python program ( [http://peterbeerli.com/classdata/ISC4304/codes Example code is in the codes section under boost_1unix.zip]); we will also look at [http://mrbook.org/blog/tutorials/make/ MrBook's stuff on Makefiles] <br />
*[[Media:isc4304boost_python2.pdf| Lecture 20 Boost-Python ]]<br />
*[[Media:isc4304cython_bradshaw.pdf| Lecture 21 Cython April 11]] [http://peterbeerli.com/classdata/ISC4304/codes/cython_integration.zip Example Codes] <br />
*Lecture 22 Cython versus Boost April 13 [http://peterbeerli.com/classdata/ISC4304/codes/deathmatch_boost_cython.zip Deathmatch_boost_cython] An excellent discussion of the Julia set(s) can be found [http://www.karlsims.com/julia.html here] and [http://acko.net/blog/how-to-fold-a-julia-fractal here]<br />
*[[Media:isc4304cpluspluscython.pdf| Lecture 23 STL/C++/Cython/Python walkthrough April 18]] [http://peterbeerli.com/classdata/ISC4304/codes/part_example_automata.zip (partial Example code)]<br />
*Lecture 24 Fortran/Parallel speed improvement walkthrough April 20 [http://peterbeerli.com/classdata/ISC4304/codes/more_on_speed_and_fortran.zip (Example code)]<br />
* FAQ about cython with an example (Philip will lead) [http://peterbeerli.com/classdata/ISC4304/codes/mock.zip (Example code)] <br />
<br><br />
<br><br />
== Old slides ==<br />
*[[Media:isc4304overview1.pdf| Lecture 1 (Overview) January 8]]<br />
*[[Media:isc4304modules2.pdf| Lecture 2 (Python Modules and Interaction with the OS) January 13]]<br />
*[[Media:isc4304containers3.pdf| Lecture 3 (Containers in python) January 15]]<br />
*[[Media:isc4304functions4.pdf| Lecture 4 (Functions) January 20]]<br />
*[[Media:isc4304textprocessing5.pdf| Lecture 5 (Text processing) January 22]]<br />
*[[Media:isc4304matplotlib6.pdf| Lecture 6 (Plotting with matplotlib) January 27]]<br />
*[[Media:isc4304numpy7.pdf| Lecture 7 (scientific computing with numpy) January 29]]<br />
*[[Media:isc4304scipy8.pdf| Lecture 8 (scientific computing with scipy) February 3]]<br />
*[[Media:isc4304classes9.pdf| Lecture 9 (Object orientation with Python 1) February 5]]<br />
*[[Media:isc4304classes10.pdf| Lecture 10 (Object orientation with Python 2) February 10]]<br />
*Lecture 11 (Solving a ODE with n variables) February 12 (download zip file from [http://people.sc.fsu.edu/~pbeerli/downloads/classes/lecture11.zip here])<br />
*[[Media:isc4304iterators12.pdf| Lecture 12 (Iterators and Generators) February 17]]<br />
*[[Media:isc4304speed.pdf| Lecture 13 (Speed) February 19]] ([[Media:EuroTutorial2011.pdf| Original Lecture]])<br />
*[[Media:isc4304debug.pdf| Lecture 14 (Debugging and Beautifcation) February 24]]<br />
*[[Media:isc4304julia.pdf| Lecture 15 (alternatives to Python: Julia) February 24]] (Complete [http://people.sc.fsu.edu/~pbeerli/downloads/classes/Julia-EuroSciPy14-mod.zip package] with IJulia notebooks) [for installation of Julia and IJulia look at [http://www.julialang.org the Julia main website] ].<br />
*[[Media:isc4304cplusplusintro.pdf| Lecture 16 C++ Pointers and such March 17]]<br />
*[[Media:isc4304cplusplusreferences.pdf| Lecture 17 C++ References March 24]]<br />
*Lecture 18 C++ references/Const/operators March 26, coding an example class: [http://courses.cms.caltech.edu/cs11/material/cpp/donnie/cpp-ops.html operator instructions]; [https://isocpp.org/wiki/faq/const-correctness Const-correctness]<br />
*Installation of Boost-Python from scratch and trial of a simple example C++/python program [http://people.sc.fsu.edu/~pbeerli/downloads/classes/classtut.zip Example code] [[Media:isc4304boost_python1.pdf| Lecture 19 Boost-Python March 31]]<br />
*[[Media:isc4304boost_python2.pdf| Lecture 20 Boost-Python April 2]]<br />
*[[Media:isc4304cython_bradshaw.pdf| Lecture 21 Cython April 7]]<br />
*Lecture 22 More Cython practice April 9 [http://people.sc.fsu.edu/~pbeerli/downloads/classes/integration.zip (Example code)] <br />
*[[Media:isc4304templates.pdf| Lecture 23 C++ templates and the STL April 14]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/template_examples.zip (Example code)]<br />
*[[Media:isc4304cpluspluscython.pdf| Lecture 24 STL/C++/Cython/Python walkthrough April 16]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/example_automata.zip (Example code)]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Main_Page&diff=1039Main Page2018-01-08T14:06:13Z<p>Peter Beerli: /* ISC-4304 Programming for Scientific Applications ([1]introduction to Python, [2] use C++ to improve speed Python code) */</p>
<hr />
<div>__NOTOC__<br />
{{DISPLAYTITLE:<span style="display: none">{{FULLPAGENAME}}</span>}}<br />
<br />
(this will slowly taking over my old site at [http://people.sc.fsu.edu/~pbeerli http://people.sc.fsu.edu/~pbeerli])<br />
<br />
This is the spring board to [http://www.peterbeerli.com Peter Beerli's] classes:<br />
<br />
'''<br />
= Current Class [Fall 2017] =<br />
== [[ISC-4304]] Programming for Scientific Applications == <br />
'''([1]introduction to Python, [2] use C++ to improve speed Python code)'''<br />
<br />
= Classes =<br />
== [[ISC-5317]] Computational Evolutionary Biology ==<br />
== [[ISC-5935PPG]] Practical Population/Phylo-Genetics Inference ==<br />
== [[ISC-4304]] Programming for Scientific Applications ==<br />
== [[ISC-3313]] Introduction to Scientific Computing using C++ ==<br />
== [[ISC-4221]] Discrete Algorithms in Scientific Computing ==<br />
<br />
= Seminars = <br />
== [[ISC-5939-03]] Markov Chain Monte Carlo in Practice Seminar ==<br />
== [[ISC-4931-01]] Junior Undergraduate Seminar Scientific Computing==<br />
<br />
= Workshops =<br />
== [[UnixRX]] UNIX and Python remedy ==<br />
<br />
= MIGRATE Tutorials =<br />
<!-- == [[migratetutorial | Migrate Tutorials Intro page]] == --><br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_lima_2016.html Tutorial for the EPONGE workshop in Lima October 3-7 2016]<br />
<br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_columbus_2017.html Tutorial for the workshop at the Ohio State University in Columbus OH February 24 2017]<br />
<br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_DC_2017.html Tutorial for the workshop at the Smithsonian Conservation Genomics Center April 28 2017]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Lab_assignments_for_ISC-4304&diff=1038Lab assignments for ISC-43042018-01-08T14:04:47Z<p>Peter Beerli: </p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2017.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
== Lab for Spring 2018 ==<br />
none assigned yet<br />
<br><br />
== Old labs ==<br />
* Lab 1: Python, learn basic python commands and write a simple function [[Media:isc4304lab1S2017.pdf|PDF]]<br />
* Lab 2: Python, simple book analysis [[Media:isc4304lab2_S2017.pdf | PDF]]<br />
* Lab 3: Python, Conway's Game of Life [[Media:isc4304lab3_S2017.pdf | PDF]] <br><br />
(Some description of Conway's Game of Life [[Media:conwaygame.pdf | PDF]])<br />
* Lab 4 Plotting with matplotlib [[Media:isc4304lab4_S2017.pdf | PDF]] <br><br />
* Lab 5 n-ODE lab [[Media:isc4304lab5S2017.pdf | PDF]] <br><br />
* Lab 6 Bayesian inference on 4-sided dice data using Python [[Media:isc4304lab6S2017.pdf | PDF]] <br><br />
* Lab 7 Bayesian inference on 4-sided dice data using C++ [[Media:isc4304lab7S2017.pdf | PDF]] <br><br />
* Lab 8 Translation of the numerical n-ODE example to C++ [[Media:isc4304lab8S2017.pdf | PDF]] <br><br />
* Lab 9 Combining Python with C++ using boost::python [[Media:isc4304lab9S2017.pdf | PDF]]<br />
* Lab 10 Speeding up a python program using Cython [[Media:isc4304lab10S2017.pdf | PDF]] Code to improve is this [http://peterbeerli.com/classdata/ISC4304/codes/mandelbrot.zip Mandelbrot Python program] (look at the lectures on cython [integration and Juliaset examples) for details how to run cython)<br />
* Lab 1: Python, learn basic python commands and write a simple function [[Media:isc4304lab1.pdf|PDF]]<br />
* Lab 2: Python, simple book analysis [[Media:isc4304lab2.pdf | PDF]]<br />
* Lab 3: Python, Conway's Game of Life [[Media:isc4304lab3.pdf | PDF]] <br><br />
* Lab 3 Addendum: Python and Matplotlib, Conway's Game of Life [[Media:isc4304lab3add.pdf | PDF]]<br />
* Lab 4 Plotting with matplotlib [[Media:isc4304lab4.pdf | PDF]] <br><br />
* Lab 5 n-ODE lab [[Media:isc4304lab5.pdf | PDF]] <br><br />
* Lab 6 Bayesian inference on 4-sided dice data using Python [[Media:isc4304lab6.pdf | PDF]] <br><br />
* Lab 7 Bayesian inference on 4-sided dice data using C++ [[Media:isc4304lab7.pdf | PDF]] <br><br />
* Lab 8 Translation of the numerical n-ODE example to C++ [[Media:isc4304lab8.pdf | PDF]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/vectordir.zip Small Vector library]<br><br />
* Lab 9 Combining Python with C++ using boost::python [[Media:isc4304lab9.pdf | PDF]]<br />
* Lab 10 Speeding up a python program using Cython [[Media:isc4304lab10.pdf | PDF]] Code to improve is this [http://people.sc.fsu.edu/~pbeerli/downloads/classes/mandelbrot.zip Mandelbrot Python program] (this example [ [http://people.sc.fsu.edu/~pbeerli/downloads/classes/integration.zip integration.zip] from the last class may help to set up the cython compile using the setup.py, it needs to be called like this: python setup.py build_ext --inplace )<br />
* Lab 11 Speeding up even more by running in parallel [[Media:isc4304lab11.pdf | PDF]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Homework_for_ISC-4304&diff=1037Homework for ISC-43042018-01-08T14:03:58Z<p>Peter Beerli: </p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2017.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
<br />
== Homework for Spring 2018 ==<br />
None assigned yet.<br />
<br />
<br><br />
== Old homework from prefious years ==<br />
*[[Media:isc4304homework1S2017.pdf| Home work 1]] <br />
*[[Media:isc4304homework2S2017.pdf| Home work 2]] <br />
*[[Media:isc4304homework3S2017.pdf| Home work 3]] (use this worksheet to turn on the homework [http://peterbeerli.com/classdata/ISC4304/codes/homework3S2017worksheet.txt homework3worksheet.txt])<br />
*[[Media:isc4304homework1.pdf| Home work 1]] <br />
*[[Media:isc4304homework2.pdf| Home work 2]] <br />
*[[Media:isc4304homework3.pdf| Home work 3]] <br />
*[[Media:isc4304homework4.pdf| Home work 4]]<br />
*[[Media:isc4304homework5.pdf| Home work 5]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=File:Isc4304overview1S2018.pdf&diff=1036File:Isc4304overview1S2018.pdf2018-01-08T14:01:54Z<p>Peter Beerli: </p>
<hr />
<div></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Notes_ISC-4304&diff=1035Notes ISC-43042018-01-08T13:41:54Z<p>Peter Beerli: </p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2018.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
<br />
[[file:peterteaching.jpg | 300px | top | right ]]<br />
<br><br />
(for Spring semester 2018)<br />
*[[Media:isc4304overview1S2018.pdf| Lecture 1 (Syllabus/Introduction) January 8]]<br />
<br />
----<br />
<br />
<br><br />
(OLD SLIDES for Spring semester 2017)<br />
*[[Media:isc4304overview1S2017.pdf| Lecture 1 (Overview) January 10]]<br />
*[[Media:isc4304modules2S2017.pdf| Lecture 2 (Python Modules and Interaction with the OS) January 12]]<br />
*[[Media:isc4304containers3S2017.pdf| Lecture 3 (Containers in python) January 17]]<br />
*[[Media:isc4304functions4S2017.pdf| Lecture 4 (Functions) January 29]]<br />
*[[Media:isc4304textprocessing+mix5S2017.pdf| Lecture 5 (Text processing) January 24]]<br />
*[[Media:isc4304matplotlib6S2017.pdf| Lecture 6 (Plotting with matplotlib) January 26]]<br />
*[[Media:isc4304numpy7S2017.pdf| Lecture 7 (scientific computing with numpy) January 31]]<br />
*[[Media:isc4304scipy8S2017.pdf| Lecture 8 (scientific computing with scipy) February 2]]<br />
*[[Media:isc4304classes9S2017.pdf| Lecture 9 (Object orientation with Python 1) February 7]]<br />
*[[Media:isc4304classes10S2017.pdf| Lecture 10 (Object orientation with Python 2) February 9]]<br />
* Tuesday February 14 2017: Question answer session on matplotlib<br />
*[[Media:isc4304iterators12S2017.pdf| Lecture 12 (Iterators and Generators) February 16]]<br />
*[[Media:isc4304debug.pdf| Lecture 13 (Debugging and Beautifcation) February 23]]<br />
*[[Media:isc4304speedS2017.pdf| Lecture 14 (Speed) February 28]] ([[Media:EuroTutorial2011.pdf| Original Lecture]])<br />
*[[Media:isc4304julia.pdf| Lecture 15 (alternatives to Python: Julia) March 2]] (Complete [http://people.sc.fsu.edu/~pbeerli/downloads/classes/Julia-EuroSciPy14-mod.zip package] with IJulia notebooks) [for installation of Julia and IJulia look at [http://www.julialang.org the Julia main website] ].<br />
*[[Media:isc4304cplusplusintro.pdf| Lecture 16 C++ Pointers and such March 21]]<br />
*[[Media:isc4304cplusplusreferences.pdf| Lecture 17 C++ References March 23]]<br />
*[[Media:isc4304STL.pdf| Lecture 18 STL March 28]]<br />
*Additional Material on const correctness and operator overloading [http://courses.cms.caltech.edu/cs11/material/cpp/donnie/cpp-ops.html operator instructions]; [https://isocpp.org/wiki/faq/const-correctness Const-correctness]<br />
* [[Media:isc4304boost_python1S2017.pdf| Lecture 19 Boost-Python March 30]] Installation of Boost-Python from scratch and trial of a simple example C++/python program ( [http://peterbeerli.com/classdata/ISC4304/codes Example code is in the codes section under boost_1unix.zip]); we will also look at [http://mrbook.org/blog/tutorials/make/ MrBook's stuff on Makefiles] <br />
*[[Media:isc4304boost_python2.pdf| Lecture 20 Boost-Python ]]<br />
*[[Media:isc4304cython_bradshaw.pdf| Lecture 21 Cython April 11]] [http://peterbeerli.com/classdata/ISC4304/codes/cython_integration.zip Example Codes] <br />
*Lecture 22 Cython versus Boost April 13 [http://peterbeerli.com/classdata/ISC4304/codes/deathmatch_boost_cython.zip Deathmatch_boost_cython] An excellent discussion of the Julia set(s) can be found [http://www.karlsims.com/julia.html here] and [http://acko.net/blog/how-to-fold-a-julia-fractal here]<br />
*[[Media:isc4304cpluspluscython.pdf| Lecture 23 STL/C++/Cython/Python walkthrough April 18]] [http://peterbeerli.com/classdata/ISC4304/codes/part_example_automata.zip (partial Example code)]<br />
*Lecture 24 Fortran/Parallel speed improvement walkthrough April 20 [http://peterbeerli.com/classdata/ISC4304/codes/more_on_speed_and_fortran.zip (Example code)]<br />
* FAQ about cython with an example (Philip will lead) [http://peterbeerli.com/classdata/ISC4304/codes/mock.zip (Example code)] <br />
<br><br />
<br><br />
== Old slides ==<br />
*[[Media:isc4304overview1.pdf| Lecture 1 (Overview) January 8]]<br />
*[[Media:isc4304modules2.pdf| Lecture 2 (Python Modules and Interaction with the OS) January 13]]<br />
*[[Media:isc4304containers3.pdf| Lecture 3 (Containers in python) January 15]]<br />
*[[Media:isc4304functions4.pdf| Lecture 4 (Functions) January 20]]<br />
*[[Media:isc4304textprocessing5.pdf| Lecture 5 (Text processing) January 22]]<br />
*[[Media:isc4304matplotlib6.pdf| Lecture 6 (Plotting with matplotlib) January 27]]<br />
*[[Media:isc4304numpy7.pdf| Lecture 7 (scientific computing with numpy) January 29]]<br />
*[[Media:isc4304scipy8.pdf| Lecture 8 (scientific computing with scipy) February 3]]<br />
*[[Media:isc4304classes9.pdf| Lecture 9 (Object orientation with Python 1) February 5]]<br />
*[[Media:isc4304classes10.pdf| Lecture 10 (Object orientation with Python 2) February 10]]<br />
*Lecture 11 (Solving a ODE with n variables) February 12 (download zip file from [http://people.sc.fsu.edu/~pbeerli/downloads/classes/lecture11.zip here])<br />
*[[Media:isc4304iterators12.pdf| Lecture 12 (Iterators and Generators) February 17]]<br />
*[[Media:isc4304speed.pdf| Lecture 13 (Speed) February 19]] ([[Media:EuroTutorial2011.pdf| Original Lecture]])<br />
*[[Media:isc4304debug.pdf| Lecture 14 (Debugging and Beautifcation) February 24]]<br />
*[[Media:isc4304julia.pdf| Lecture 15 (alternatives to Python: Julia) February 24]] (Complete [http://people.sc.fsu.edu/~pbeerli/downloads/classes/Julia-EuroSciPy14-mod.zip package] with IJulia notebooks) [for installation of Julia and IJulia look at [http://www.julialang.org the Julia main website] ].<br />
*[[Media:isc4304cplusplusintro.pdf| Lecture 16 C++ Pointers and such March 17]]<br />
*[[Media:isc4304cplusplusreferences.pdf| Lecture 17 C++ References March 24]]<br />
*Lecture 18 C++ references/Const/operators March 26, coding an example class: [http://courses.cms.caltech.edu/cs11/material/cpp/donnie/cpp-ops.html operator instructions]; [https://isocpp.org/wiki/faq/const-correctness Const-correctness]<br />
*Installation of Boost-Python from scratch and trial of a simple example C++/python program [http://people.sc.fsu.edu/~pbeerli/downloads/classes/classtut.zip Example code] [[Media:isc4304boost_python1.pdf| Lecture 19 Boost-Python March 31]]<br />
*[[Media:isc4304boost_python2.pdf| Lecture 20 Boost-Python April 2]]<br />
*[[Media:isc4304cython_bradshaw.pdf| Lecture 21 Cython April 7]]<br />
*Lecture 22 More Cython practice April 9 [http://people.sc.fsu.edu/~pbeerli/downloads/classes/integration.zip (Example code)] <br />
*[[Media:isc4304templates.pdf| Lecture 23 C++ templates and the STL April 14]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/template_examples.zip (Example code)]<br />
*[[Media:isc4304cpluspluscython.pdf| Lecture 24 STL/C++/Cython/Python walkthrough April 16]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/example_automata.zip (Example code)]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=File:Syllabus-ISC4304-S2018.pdf&diff=1034File:Syllabus-ISC4304-S2018.pdf2018-01-08T04:46:34Z<p>Peter Beerli: </p>
<hr />
<div></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-4304&diff=1033ISC-43042018-01-08T04:45:59Z<p>Peter Beerli: </p>
<hr />
<div>== Programming for Science Applications==<br />
[[File:eniac4.jpg|left|top]]<br />
<div style="clear: both"></div><br />
This course provides knowledge of a scripting language (python) that serves as a front-end to popular packages and frameworks, along with a compiled language (C++). Students will study and practice object-oriented scientific programming with the scripting and compiled language. In the laboratory component of the course, students will apply the concepts learned in several scientific applications.<br />
<br />
* [[Media:Syllabus-ISC4304-S2018.pdf | Syllabus]]<br />
* [[Notes ISC-4304 | Class notes and slides]]<br />
* [[Homework for ISC-4304 | Homework ]]<br />
* [[Lab assignments for ISC-4304 | Lab assignments]]<br />
* [[Resources for ISC-4304 | Resources]]<br />
* [[FunExamples | Fun examples we will run in class]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Notes_ISC-4304&diff=1032Notes ISC-43042018-01-08T04:45:21Z<p>Peter Beerli: </p>
<hr />
<div>([[Media:Syllabus-ISC4304-S2018.pdf | Syllabus]] [[Notes ISC-4304 | Classnotes]] [[Homework for ISC-4304 | Homework ]] [[Lab assignments for ISC-4304 | Lab]] [[Resources for ISC-4304 | Resources]] [[FunExamples | Fun]])<br />
<br />
<br />
[[file:peterteaching.jpg | 300px | top | center ]]<br />
<br><br />
(for Spring semester 2017)<br />
*[[Media:isc4304overview1S2017.pdf| Lecture 1 (Overview) January 10]]<br />
*[[Media:isc4304modules2S2017.pdf| Lecture 2 (Python Modules and Interaction with the OS) January 12]]<br />
*[[Media:isc4304containers3S2017.pdf| Lecture 3 (Containers in python) January 17]]<br />
*[[Media:isc4304functions4S2017.pdf| Lecture 4 (Functions) January 29]]<br />
*[[Media:isc4304textprocessing+mix5S2017.pdf| Lecture 5 (Text processing) January 24]]<br />
*[[Media:isc4304matplotlib6S2017.pdf| Lecture 6 (Plotting with matplotlib) January 26]]<br />
*[[Media:isc4304numpy7S2017.pdf| Lecture 7 (scientific computing with numpy) January 31]]<br />
*[[Media:isc4304scipy8S2017.pdf| Lecture 8 (scientific computing with scipy) February 2]]<br />
*[[Media:isc4304classes9S2017.pdf| Lecture 9 (Object orientation with Python 1) February 7]]<br />
*[[Media:isc4304classes10S2017.pdf| Lecture 10 (Object orientation with Python 2) February 9]]<br />
* Tuesday February 14 2017: Question answer session on matplotlib<br />
*[[Media:isc4304iterators12S2017.pdf| Lecture 12 (Iterators and Generators) February 16]]<br />
*[[Media:isc4304debug.pdf| Lecture 13 (Debugging and Beautifcation) February 23]]<br />
*[[Media:isc4304speedS2017.pdf| Lecture 14 (Speed) February 28]] ([[Media:EuroTutorial2011.pdf| Original Lecture]])<br />
*[[Media:isc4304julia.pdf| Lecture 15 (alternatives to Python: Julia) March 2]] (Complete [http://people.sc.fsu.edu/~pbeerli/downloads/classes/Julia-EuroSciPy14-mod.zip package] with IJulia notebooks) [for installation of Julia and IJulia look at [http://www.julialang.org the Julia main website] ].<br />
*[[Media:isc4304cplusplusintro.pdf| Lecture 16 C++ Pointers and such March 21]]<br />
*[[Media:isc4304cplusplusreferences.pdf| Lecture 17 C++ References March 23]]<br />
*[[Media:isc4304STL.pdf| Lecture 18 STL March 28]]<br />
*Additional Material on const correctness and operator overloading [http://courses.cms.caltech.edu/cs11/material/cpp/donnie/cpp-ops.html operator instructions]; [https://isocpp.org/wiki/faq/const-correctness Const-correctness]<br />
* [[Media:isc4304boost_python1S2017.pdf| Lecture 19 Boost-Python March 30]] Installation of Boost-Python from scratch and trial of a simple example C++/python program ( [http://peterbeerli.com/classdata/ISC4304/codes Example code is in the codes section under boost_1unix.zip]); we will also look at [http://mrbook.org/blog/tutorials/make/ MrBook's stuff on Makefiles] <br />
*[[Media:isc4304boost_python2.pdf| Lecture 20 Boost-Python ]]<br />
*[[Media:isc4304cython_bradshaw.pdf| Lecture 21 Cython April 11]] [http://peterbeerli.com/classdata/ISC4304/codes/cython_integration.zip Example Codes] <br />
*Lecture 22 Cython versus Boost April 13 [http://peterbeerli.com/classdata/ISC4304/codes/deathmatch_boost_cython.zip Deathmatch_boost_cython] An excellent discussion of the Julia set(s) can be found [http://www.karlsims.com/julia.html here] and [http://acko.net/blog/how-to-fold-a-julia-fractal here]<br />
*[[Media:isc4304cpluspluscython.pdf| Lecture 23 STL/C++/Cython/Python walkthrough April 18]] [http://peterbeerli.com/classdata/ISC4304/codes/part_example_automata.zip (partial Example code)]<br />
*Lecture 24 Fortran/Parallel speed improvement walkthrough April 20 [http://peterbeerli.com/classdata/ISC4304/codes/more_on_speed_and_fortran.zip (Example code)]<br />
* FAQ about cython with an example (Philip will lead) [http://peterbeerli.com/classdata/ISC4304/codes/mock.zip (Example code)] <br />
<br><br />
<br><br />
== Old slides ==<br />
*[[Media:isc4304overview1.pdf| Lecture 1 (Overview) January 8]]<br />
*[[Media:isc4304modules2.pdf| Lecture 2 (Python Modules and Interaction with the OS) January 13]]<br />
*[[Media:isc4304containers3.pdf| Lecture 3 (Containers in python) January 15]]<br />
*[[Media:isc4304functions4.pdf| Lecture 4 (Functions) January 20]]<br />
*[[Media:isc4304textprocessing5.pdf| Lecture 5 (Text processing) January 22]]<br />
*[[Media:isc4304matplotlib6.pdf| Lecture 6 (Plotting with matplotlib) January 27]]<br />
*[[Media:isc4304numpy7.pdf| Lecture 7 (scientific computing with numpy) January 29]]<br />
*[[Media:isc4304scipy8.pdf| Lecture 8 (scientific computing with scipy) February 3]]<br />
*[[Media:isc4304classes9.pdf| Lecture 9 (Object orientation with Python 1) February 5]]<br />
*[[Media:isc4304classes10.pdf| Lecture 10 (Object orientation with Python 2) February 10]]<br />
*Lecture 11 (Solving a ODE with n variables) February 12 (download zip file from [http://people.sc.fsu.edu/~pbeerli/downloads/classes/lecture11.zip here])<br />
*[[Media:isc4304iterators12.pdf| Lecture 12 (Iterators and Generators) February 17]]<br />
*[[Media:isc4304speed.pdf| Lecture 13 (Speed) February 19]] ([[Media:EuroTutorial2011.pdf| Original Lecture]])<br />
*[[Media:isc4304debug.pdf| Lecture 14 (Debugging and Beautifcation) February 24]]<br />
*[[Media:isc4304julia.pdf| Lecture 15 (alternatives to Python: Julia) February 24]] (Complete [http://people.sc.fsu.edu/~pbeerli/downloads/classes/Julia-EuroSciPy14-mod.zip package] with IJulia notebooks) [for installation of Julia and IJulia look at [http://www.julialang.org the Julia main website] ].<br />
*[[Media:isc4304cplusplusintro.pdf| Lecture 16 C++ Pointers and such March 17]]<br />
*[[Media:isc4304cplusplusreferences.pdf| Lecture 17 C++ References March 24]]<br />
*Lecture 18 C++ references/Const/operators March 26, coding an example class: [http://courses.cms.caltech.edu/cs11/material/cpp/donnie/cpp-ops.html operator instructions]; [https://isocpp.org/wiki/faq/const-correctness Const-correctness]<br />
*Installation of Boost-Python from scratch and trial of a simple example C++/python program [http://people.sc.fsu.edu/~pbeerli/downloads/classes/classtut.zip Example code] [[Media:isc4304boost_python1.pdf| Lecture 19 Boost-Python March 31]]<br />
*[[Media:isc4304boost_python2.pdf| Lecture 20 Boost-Python April 2]]<br />
*[[Media:isc4304cython_bradshaw.pdf| Lecture 21 Cython April 7]]<br />
*Lecture 22 More Cython practice April 9 [http://people.sc.fsu.edu/~pbeerli/downloads/classes/integration.zip (Example code)] <br />
*[[Media:isc4304templates.pdf| Lecture 23 C++ templates and the STL April 14]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/template_examples.zip (Example code)]<br />
*[[Media:isc4304cpluspluscython.pdf| Lecture 24 STL/C++/Cython/Python walkthrough April 16]] [http://people.sc.fsu.edu/~pbeerli/downloads/classes/example_automata.zip (Example code)]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-4304&diff=1031ISC-43042018-01-08T04:44:34Z<p>Peter Beerli: </p>
<hr />
<div>== Programming for Science Applications==<br />
[[File:eniac4.jpg|left|top]]<br />
<div style="clear: both"></div><br />
This course provides knowledge of a scripting language (python) that serves as a front-end to popular packages and frameworks, along with a compiled language (C++). Students will study and practice object-oriented scientific programming with the scripting and compiled language. In the laboratory component of the course, students will apply the concepts learned in several scientific applications.<br />
<br />
* [[Media:Syllabus-ISC4304-S201S.pdf | Syllabus]]<br />
* [[Notes ISC-4304 | Class notes and slides]]<br />
* [[Homework for ISC-4304 | Homework ]]<br />
* [[Lab assignments for ISC-4304 | Lab assignments]]<br />
* [[Resources for ISC-4304 | Resources]]<br />
* [[FunExamples | Fun examples we will run in class]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=MediaWiki:Sidebar&diff=1030MediaWiki:Sidebar2017-12-16T16:41:52Z<p>Peter Beerli: </p>
<hr />
<div>* navigation<br />
#** mainpage|mainpage-description<br />
** mainpage|Overview<br />
** ISC-4304|Current Class<br />
** ISC-4931-01|Current Seminar<br />
** heroes|Heroes<br />
#** portal-url|portal<br />
#** currentevents-url|currentevents<br />
#** recentchanges-url|recentchanges<br />
#** randompage-url|randompage<br />
#** helppage|help<br />
* SEARCH<br />
* TOOLBOX<br />
* LANGUAGES</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Main_Page&diff=1029Main Page2017-12-16T16:38:18Z<p>Peter Beerli: </p>
<hr />
<div>__NOTOC__<br />
{{DISPLAYTITLE:<span style="display: none">{{FULLPAGENAME}}</span>}}<br />
<br />
(this will slowly taking over my old site at [http://people.sc.fsu.edu/~pbeerli http://people.sc.fsu.edu/~pbeerli])<br />
<br />
This is the spring board to [http://www.peterbeerli.com Peter Beerli's] classes:<br />
<br />
'''<br />
= Current Class [Fall 2017] =<br />
== [[ISC-4304]] Programming for Scientific Applications ([1]introduction to Python, [2] use C++ to improve speed Python code) ==<br />
'''<br />
<br />
= Classes =<br />
== [[ISC-5317]] Computational Evolutionary Biology ==<br />
== [[ISC-5935PPG]] Practical Population/Phylo-Genetics Inference ==<br />
== [[ISC-4304]] Programming for Scientific Applications ==<br />
== [[ISC-3313]] Introduction to Scientific Computing using C++ ==<br />
== [[ISC-4221]] Discrete Algorithms in Scientific Computing ==<br />
<br />
= Seminars = <br />
== [[ISC-5939-03]] Markov Chain Monte Carlo in Practice Seminar ==<br />
== [[ISC-4931-01]] Junior Undergraduate Seminar Scientific Computing==<br />
<br />
= Workshops =<br />
== [[UnixRX]] UNIX and Python remedy ==<br />
<br />
= MIGRATE Tutorials =<br />
<!-- == [[migratetutorial | Migrate Tutorials Intro page]] == --><br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_lima_2016.html Tutorial for the EPONGE workshop in Lima October 3-7 2016]<br />
<br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_columbus_2017.html Tutorial for the workshop at the Ohio State University in Columbus OH February 24 2017]<br />
<br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_DC_2017.html Tutorial for the workshop at the Smithsonian Conservation Genomics Center April 28 2017]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1028ISC-53172017-11-03T14:07:59Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100317_notes.pdf 100317_notes.pdf] -<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] <br />
*Current lecture and notes: Same as last lecture notes (continue) <br />
*Last few lecture: [http://peterbeerli.com/classdata/ISC5317/coalescence1.pdf coalescence1.pdf] ,<br />
[http://peterbeerli.com/classdata/ISC5317/coalescence2.pdf coalescence2.pdf] <br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/Laura_Kubatko_speciestree_mbl2017.pdf Laura_Kubatko_speciestree_mbl2017.pdf] --><br />
*Last three lectures: [http://peterbeerli.com/classdata/ISC5317/Laura_Kubatko_speciestree_mbl2017.pdf Laura_Kubatko_speciestree_mbl2017.pdf], [http://peterbeerli.com/classdata/ISC5317/modelselection.pdf modelselection.pdf], [http://peterbeerli.com/classdata/ISC5317/bootstrap.pdf bootstrap.pdf], [http://phylo.bio.ku.edu/mephytis/boot-sample.html Mark Holder's bootstrap example] <br />
<br />
<!-- [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] --><br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1027ISC-53172017-11-03T13:43:17Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100317_notes.pdf 100317_notes.pdf] -<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] <br />
*Current lecture and notes: Same as last lecture notes (continue) <br />
*Last few lecture: [http://peterbeerli.com/classdata/ISC5317/coalescence1.pdf coalescence1.pdf] ,<br />
[http://peterbeerli.com/classdata/ISC5317/coalescence2.pdf coalescence2.pdf] <br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/Laura_Kubatko_speciestree_mbl2017.pdf Laura_Kubatko_speciestree_mbl2017.pdf] --><br />
*Last three lectures: [http://peterbeerli.com/classdata/ISC5317/Laura_Kubatko_speciestree_mbl2017.pdf Laura_Kubatko_speciestree_mbl2017.pdf], [http://peterbeerli.com/classdata/ISC5317/modelselection.pdf modelselection.pdf], [http://peterbeerli.com/classdata/ISC5317/bootstrap.pdf bootstrap.pdf] <br />
<br />
<!-- [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] --><br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Main_Page&diff=1026Main Page2017-10-28T14:34:25Z<p>Peter Beerli: </p>
<hr />
<div>__NOTOC__<br />
{{DISPLAYTITLE:<span style="display: none">{{FULLPAGENAME}}</span>}}<br />
<br />
(this will slowly taking over my old site at [http://people.sc.fsu.edu/~pbeerli http://people.sc.fsu.edu/~pbeerli])<br />
<br />
This is the spring board to [http://www.peterbeerli.com Peter Beerli's] classes:<br />
<br />
'''<br />
= Current Class [Fall 2017] =<br />
== [[ISC-5317]] Computational Evolutionary Biology ==<br />
'''<br />
<br />
= Classes =<br />
== [[ISC-5935PPG]] Practical Population/Phylo-Genetics Inference ==<br />
== [[ISC-4304]] Programming for Scientific Applications ==<br />
== [[ISC-3313]] Introduction to Scientific Computing using C++ ==<br />
== [[ISC-4221]] Discrete Algorithms in Scientific Computing ==<br />
== [[ISC-5317]] Computational Evolutionary Biology==<br />
<br />
= Seminars = <br />
== [[ISC-5939-03]] Markov Chain Monte Carlo in Practice Seminar ==<br />
== [[ISC-4931-01]] Junior Undergraduate Seminar Scientific Computing==<br />
<br />
= Workshops =<br />
== [[UnixRX]] UNIX and Python remedy ==<br />
<br />
= MIGRATE Tutorials =<br />
<!-- == [[migratetutorial | Migrate Tutorials Intro page]] == --><br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_lima_2016.html Tutorial for the EPONGE workshop in Lima October 3-7 2016]<br />
<br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_columbus_2017.html Tutorial for the workshop at the Ohio State University in Columbus OH February 24 2017]<br />
<br />
[http://peterbeerli.com/classdata/workshops/migratetutorial_DC_2017.html Tutorial for the workshop at the Smithsonian Conservation Genomics Center April 28 2017]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1025ISC-53172017-10-27T14:47:41Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100317_notes.pdf 100317_notes.pdf] -<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] <br />
*Current lecture and notes: Same as last lecture notes (continue) --><br />
*Last few lecture: [http://peterbeerli.com/classdata/ISC5317/coalescence1.pdf coalescence1.pdf] ,<br />
[http://peterbeerli.com/classdata/ISC5317/coalescence2.pdf coalescence2.pdf] <br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/Laura_Kubatko_speciestree_mbl2017.pdf Laura_Kubatko_speciestree_mbl2017.pdf] <br />
<br />
<!-- [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] --><br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1024ISC-53172017-10-10T14:41:46Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100317_notes.pdf 100317_notes.pdf] --><br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] <br />
*Current lecture and notes: Same as last lecture notes (continue)<br />
<!-- [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] --><br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1023ISC-53172017-10-05T14:50:11Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] --> <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100317_notes.pdf 100317_notes.pdf] <br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/100517_bayeshandout.pdf 100517_bayeshandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100517_notes.pdf 100517_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1022ISC-53172017-10-03T14:38:46Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] --><br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] <br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/100317_notes.pdf 100317_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1021ISC-53172017-09-28T14:33:59Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] --><br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092817_likehandout.pdf 092817_likehandout.pdf], [http://peterbeerli.com/classdata/ISC5317/092817_notes.pdf 092817_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1020ISC-53172017-09-26T14:41:06Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
<!-- *Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] --><br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117_notes.pdf] <br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092617_mutation2.pdf 092617_mutation2.pdf], [http://peterbeerli.com/classdata/ISC5317/092617_notes.pdf 092617_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1019ISC-53172017-09-21T14:31:55Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/092117_mutation1.pdf 092117_mutation1.pdf], [http://peterbeerli.com/classdata/ISC5317/092117_notes.pdf 092117-besttree_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1018ISC-53172017-09-19T14:50:41Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf],[http://peterbeerli.com/classdata/ISC5317/082917_notes.pdf 802917_notes.pdf] <br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/091917_besttree.pdf 091917_bestree.pdf], [http://peterbeerli.com/classdata/ISC5317/091917_notes.pdf 091917-besttree_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1017ISC-53172017-09-05T06:57:48Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf],[http://peterbeerli.com/classdata/ISC5317/082917_notes.pdf 802917_notes.pdf] <br />
*Current notes: [http://peterbeerli.com/classdata/ISC5317/090517-parsimony.pdf 090517-parsimony.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1016ISC-53172017-09-05T06:56:05Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Last lecture and notes: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf], *Current notes: [http://peterbeerli.com/classdata/ISC5317/090517-parsimony.pdf 090517-parsimony.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1015ISC-53172017-08-31T14:11:51Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf], [http://peterbeerli.com/classdata/ISC5317/082917_notes.pdf 802917_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
* [[Heroes]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1014ISC-53172017-08-31T14:10:40Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture and notes: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf], [http://peterbeerli.com/classdata/ISC5317/082917_notes.pdf 802917_notes.pdf] <br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1013ISC-53172017-08-31T14:07:20Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|right]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf]<br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1012ISC-53172017-08-31T14:03:38Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf]<br />
* [http://peterbeerli.com/classdata/ISC5317 Lectures]<br />
* [http://peterbeerli.com/classdata/ISC5317/assignments Assignments]<br />
* [http://peterbeerli.com/classdata/ISC5317/codes Codes]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1011ISC-53172017-08-31T13:28:48Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf]<br />
[http://peterbeerli.com/classdata/ISC5317 Lectures Directory]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1010ISC-53172017-08-31T13:27:50Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
== Current class notes ==<br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf]<br />
[[Lectures]]<br />
</p></span><br />
<br />
<br />
== Old class notes ==<br />
* [[Reading]] <br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]]</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1009ISC-53172017-08-29T14:44:42Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture: [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf]<br />
</p></span><br />
<!-- * [[Reading]]<br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]] --></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1008ISC-53172017-08-29T14:44:14Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
<span><p><br />
* [[Syllabus]]<br />
*Current lecture: [ [http://peterbeerli.com/classdata/ISC5317/082917_trees.pdf 802917_trees.pdf]<br />
</p></span><br />
<!-- * [[Reading]]<br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]] --></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1007ISC-53172017-08-29T14:40:20Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br><br />
'''We meet in room 422 in Dirac<br />
'''<br><br />
<span><p><br />
* [[Syllabus]]<br />
</p></span><br />
<!-- * [[Reading]]<br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]] --></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Syllabus&diff=1006Syllabus2017-08-28T13:48:31Z<p>Peter Beerli: /* Grading */</p>
<hr />
<div>ISC5317/ISC4933:<br />
<br />
= Computational Evolutionary Biology =<br />
<br />
Section marked with '''*''' differentiate between the graduate section requirements and the undergraduate section requirements<br />
<br />
== Class Meeting ==<br />
<br />
Lectures: Tuesdays and Thursdays 11:00AM-12:15 PM Dirac Science Library Room 152<br />
<br />
== Instructor ==<br />
<br />
Peter Beerli<br> Office: 150-T DSL<br> Email: beerli@fsu.edu<br> Phone: (850) 559-9664<br />
<br />
== Class Assistant ==<br />
<br />
Kyle Shaw<br> Office: 150-J DSL<br> Email: shawk3@outlook.com<br> Phone: TBA<br />
<br />
== Office Hours ==<br />
<br />
* Peter Beerli: by appointment (email: beerli@fsu.edu or text to 850 559 9664); or just come to my office, If do not have a meeting I will have time for you.<br />
* Kyle Shaw: we will set up an open lab session every week so that students can get help on python and the assignments.<br />
<br />
== Objectives ==<br />
<br />
This course will introduce students to methods used in phylogenetics and population genetics and writing computer programs using such methods. Primary objectives of the course are:<br />
<br />
# to expose students to a large set of modern methods used in the field of theoretical evolutionary biology, and learn about the details of often used methods in phylogenetic analysis and population genetics analysis.<br />
# to introduce students to the programming aspects of the field. Students will learn and use the programming language Python to develop scripts and to understand details of the methods.<br />
# to empower students to develop programming and analysis skills that involve development of scripts to change data format, execute applications, and analyze results.<br />
<br />
== Content ==<br />
<br />
Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. The students will get hands-on experience in developing computational software implementing these methods. We expect that the students leave the course with the necessary skills to develop their own ideas and are able to develop projects that are based on simulated data sets and scripts.<br />
<br />
== Textbook ==<br />
<br />
We will have no textbook, but we have extensive handouts available through the course website.<br />
<br />
== Grading ==<br />
<br />
* Grades will be based on students’ execution of the 5 (programming) assignments, each of which involves understanding the algorithms, code design, and program documentation <br>[100 points each<br>]<br />
* Either two students or a single student will work on a project on their own during the last four weeks of the semester and give a short presentation of their work during the last second two classes periods. I expect that group projects are twice as large as single student projects <br>[100 points for the report and 100 points for the presentation]<br />
* We will have a theory test on November 7th (midterm). <br>[100 points]<br />
* There will be no final exam, the project substitutes for a final examination. The total number of points is 800.<br />
<br />
'''*''' A student who accumulates 90% or more of the possible points will receive a grade of “A.” A student who accumulates between 80% and 89% of the possible points will receive a grade of “B.” A student who accumulates between 70% and 79% of the possible points will receive a grade of “C.” A student who accumulates between 60% and 69% of the possible points will receive a grade of “D”, and a student who accumulates less than 60% of the possible points will receive a grade of “F”. The grade of undergraduate student is calculated as 110% of the graduate grade, for example if the grade is a total of 745 points, a graduate student will receive 655/800= 0.81875 <math>\rightarrow</math> B; an undergraduate student will receive 655/800*1.1= 0.900625 <math>\rightarrow</math> A.<br />
<br />
== Missed/Late Assignments ==<br />
<br />
Deadlines for assignments will be announced in class; late assignments will be accepted for full grade only in cases of illness or death in the family. 5% of the total points (100pt) are deducted per day for late assignments.<br />
<br />
== University Attendance Policy ==<br />
<br />
Excused absences include documented illness, deaths in the family and other documented crises, call to active military duty or jury duty, religious holy days, and official University activities. These absences will be accommodated in a way that does not arbitrarily penalize students who have a valid excuse. Consideration will also be given to students whose dependent children experience serious illness.<br />
<br />
== Academic Honor Policy ==<br />
<br />
The Florida State University Academic Honor Policy outlines the University’s expectations for the integrity of students’ academic work, the procedures for resolving alleged violations of those expectations, and the rights and responsibilities of students and faculty members throughout the process. Students are responsible for reading the Academic Honor Policy and for living up to their pledge to “. . . be honest and truthful and ... <br>[to<br>] strive for personal and institutional integrity at Florida State University.&quot; (Florida State University Academic Honor Policy, found at http://dof.fsu.edu/honorpolicy.htm.)<br />
<br />
== Americans With Disabilities Act ==<br />
<br />
Students with disabilities needing academic accommodation should: (1) register with and provide documentation to the Student Disability Resource Center; and (2) bring a letter to the instructor indicating the need for accommodation and what type. Please note that instructors are not allowed to provide classroom accommodation to a student until appropriate verification from the Student Disability Resource Center has been provided. This syllabus and other class materials are available in alternative format upon request. For more information about services available to FSU students with disabilities, contact the:<br />
<br />
== Tutoring in class ==<br />
<br />
The TA will have a weekly session of two hours to help with assignments and Python tutoring, use this resource.<br />
<br />
== Free Tutoring from FSU ==<br />
<br />
For tutoring and writing help in any course at Florida State University, visit the Academic Center for Excellence (ACE) Tutoring Services’ comprehensive list of tutoring options - see http://ace.fsu.edu/tutoring or contact tutor@fsu.edu for more information. High-quality tutoring is available by appointment and on a walk-in basis. These services are offered by tutors trained to encourage the highest level of individual academic success while upholding personal academic integrity.<br />
<br />
== Syllabus Change Policy ==<br />
<br />
Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice.<br />
<br />
== Lectures: Topic overview ==<br />
<br />
# Processes and patterns<br />
#* Population genetics: Wright-Fisher population models, coalescence theory;<br />
#* Phylogenetics: tree structures, speciation, Gene tree versus Species tree<br />
#* Mutation models: mutation/substitution model<br />
#* Simulation of data<br />
# Inference:<br />
#* Parsimony and Distance methods<br />
#* Maximum likelihood, Bayesian inference, Monte Carlo, Markov chain Monte Carlo,<br />
#* Model selection<br />
#* Bootstrap/Jacknife<br />
<br />
Each topic will include computational algorithms, problematic aspects such as convergence, biases, main focus will be on Bayesian and maximum likelihood methods.<br />
<br />
== Assignments ==<br />
<br />
This list of assignments is an example, difficulty of assignments will depend on the overall class programming skills. Each assignment topic will be introduced in detail during class. The final set of assignments is not specified yet but it will look similar to the ones shown below:<br />
<br />
# Read and write a tree structure<br />
# Simulate data on a tree<br />
# Simulate data using the coalescent<br />
# Construct an ABC sampler to estimate the effective population size<br />
# Model selection using the program MIGRATE<br />
# Project: The project will discuss either (1) a complex analysis of data or (2) software development or (3) a theory section we did not discuss. The project consists of two parts, a report (of not more than 8 pages) and a presentation of 10 minutes. We will develop ideas for the project during class.<br />
<br />
* Undergraduate students can leave out one of the assignments (1-5).<br />
<br />
== Lecture Schedule ==<br />
<br />
# Introduction. Trees and tree representation (Aug. 29)<br />
# Python and trees (Aug. 31)<br />
# Parsimony (Sep 5)<br />
# Python and parsimony (Sep 7)<br />
# Searching for the best tree(s) (Sep 12)<br />
# Substitution models and distance (Sep 14)<br />
# Substitution models general Sep 19)<br />
# Substitution model exercise Sep 21)<br />
# Rate variation and more substitution models Sep 26)<br />
# Maximum Likelihood (Sep 28)<br />
# Maximum Likelihood (Oct 3)<br />
# Bayesian inference (Oct 5)<br />
# Markov chain Monte Carlo (Oct 10)<br />
# ABC – approximate Bayesian computing (Oct 12)<br />
# The coalescent (Oct 17)<br />
# Coalescent simulation and extensions to the coalescent (Oct 19)<br />
# Gene tree vs Species tree (Oct 24)<br />
# Gene tree vs Species tree (Oct 26)<br />
# Model Selection (Oct 31)<br />
# Bootstrap/Jacknife (Nov 2)<br />
# Review session (Nov 7)<br />
# Mid term (Nov 9)<br />
# Project (Nov 14)<br />
# Project (Nov 16)<br />
# Project (Nov 21)<br />
# Project (Nov 28)<br />
# Project (Nov 30)<br />
# Presentation (Dec 5)<br />
# Presentation (Dec 7)</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=Syllabus&diff=1005Syllabus2017-08-28T13:45:23Z<p>Peter Beerli: Created page with "ISC5317/ISC4933: = Computational Evolutionary Biology = Section marked with '''*''' differentiate between the graduate section requirements and the undergraduate section req..."</p>
<hr />
<div>ISC5317/ISC4933:<br />
<br />
= Computational Evolutionary Biology =<br />
<br />
Section marked with '''*''' differentiate between the graduate section requirements and the undergraduate section requirements<br />
<br />
== Class Meeting ==<br />
<br />
Lectures: Tuesdays and Thursdays 11:00AM-12:15 PM Dirac Science Library Room 152<br />
<br />
== Instructor ==<br />
<br />
Peter Beerli<br> Office: 150-T DSL<br> Email: beerli@fsu.edu<br> Phone: (850) 559-9664<br />
<br />
== Class Assistant ==<br />
<br />
Kyle Shaw<br> Office: 150-J DSL<br> Email: shawk3@outlook.com<br> Phone: TBA<br />
<br />
== Office Hours ==<br />
<br />
* Peter Beerli: by appointment (email: beerli@fsu.edu or text to 850 559 9664); or just come to my office, If do not have a meeting I will have time for you.<br />
* Kyle Shaw: we will set up an open lab session every week so that students can get help on python and the assignments.<br />
<br />
== Objectives ==<br />
<br />
This course will introduce students to methods used in phylogenetics and population genetics and writing computer programs using such methods. Primary objectives of the course are:<br />
<br />
# to expose students to a large set of modern methods used in the field of theoretical evolutionary biology, and learn about the details of often used methods in phylogenetic analysis and population genetics analysis.<br />
# to introduce students to the programming aspects of the field. Students will learn and use the programming language Python to develop scripts and to understand details of the methods.<br />
# to empower students to develop programming and analysis skills that involve development of scripts to change data format, execute applications, and analyze results.<br />
<br />
== Content ==<br />
<br />
Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. The students will get hands-on experience in developing computational software implementing these methods. We expect that the students leave the course with the necessary skills to develop their own ideas and are able to develop projects that are based on simulated data sets and scripts.<br />
<br />
== Textbook ==<br />
<br />
We will have no textbook, but we have extensive handouts available through the course website.<br />
<br />
== Grading ==<br />
<br />
* Grades will be based on students’ execution of the 5 (programming) assignments, each of which involves understanding the algorithms, code design, and program documentation <br>[100 points each<br>]<br />
* Either two students or a single student will work on a project on their own during the last 4 weeks of the semester and give a short presentation of their work during the last second two classes periods. I expect that group projects are twice as large as single student projects <br>[100 points for the report and 100 points for the presentation<br>]<br />
* We will have a theory test on November 7th (midterm). <br>[100 points<br>]<br />
* There will be no final exam, the project substitutes for a final examination. The total number of points is 800.<br />
<br />
'''*''' A student who accumulates 90% or more of the possible points will receive a grade of “A”, a student who accumulates between 80% and 89% of the possible points will receive a grade of “B”, a student who accumulates between 70% and 79% of the possible points will receive a grade of “C”, a student who accumulates between 60% and 69% of the possible points will receive a grade of “D”, and a student who accumulates less than 60% of the possible points will receive a grade of “F”. The grade of ndergraduate student is calculated as 110% of the graduate grade, for example if the grade is a total of 745 points, a graduate student will receive 655/800= 0.81875 <math>\rightarrow</math> B; an undergraduate student will receive 655/800*1.1= 0.900625 <math>\rightarrow</math> A.<br />
<br />
== Missed/Late Assignments ==<br />
<br />
Deadlines for assignments will be announced in class; late assignments will be accepted for full grade only in cases of illness or death in the family. 5% of the total points (100pt) are deducted per day for late assignments.<br />
<br />
== University Attendance Policy ==<br />
<br />
Excused absences include documented illness, deaths in the family and other documented crises, call to active military duty or jury duty, religious holy days, and official University activities. These absences will be accommodated in a way that does not arbitrarily penalize students who have a valid excuse. Consideration will also be given to students whose dependent children experience serious illness.<br />
<br />
== Academic Honor Policy ==<br />
<br />
The Florida State University Academic Honor Policy outlines the University’s expectations for the integrity of students’ academic work, the procedures for resolving alleged violations of those expectations, and the rights and responsibilities of students and faculty members throughout the process. Students are responsible for reading the Academic Honor Policy and for living up to their pledge to “. . . be honest and truthful and ... <br>[to<br>] strive for personal and institutional integrity at Florida State University.&quot; (Florida State University Academic Honor Policy, found at http://dof.fsu.edu/honorpolicy.htm.)<br />
<br />
== Americans With Disabilities Act ==<br />
<br />
Students with disabilities needing academic accommodation should: (1) register with and provide documentation to the Student Disability Resource Center; and (2) bring a letter to the instructor indicating the need for accommodation and what type. Please note that instructors are not allowed to provide classroom accommodation to a student until appropriate verification from the Student Disability Resource Center has been provided. This syllabus and other class materials are available in alternative format upon request. For more information about services available to FSU students with disabilities, contact the:<br />
<br />
== Tutoring in class ==<br />
<br />
The TA will have a weekly session of two hours to help with assignments and Python tutoring, use this resource.<br />
<br />
== Free Tutoring from FSU ==<br />
<br />
For tutoring and writing help in any course at Florida State University, visit the Academic Center for Excellence (ACE) Tutoring Services’ comprehensive list of tutoring options - see http://ace.fsu.edu/tutoring or contact tutor@fsu.edu for more information. High-quality tutoring is available by appointment and on a walk-in basis. These services are offered by tutors trained to encourage the highest level of individual academic success while upholding personal academic integrity.<br />
<br />
== Syllabus Change Policy ==<br />
<br />
Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice.<br />
<br />
== Lectures: Topic overview ==<br />
<br />
# Processes and patterns<br />
#* Population genetics: Wright-Fisher population models, coalescence theory;<br />
#* Phylogenetics: tree structures, speciation, Gene tree versus Species tree<br />
#* Mutation models: mutation/substitution model<br />
#* Simulation of data<br />
# Inference:<br />
#* Parsimony and Distance methods<br />
#* Maximum likelihood, Bayesian inference, Monte Carlo, Markov chain Monte Carlo,<br />
#* Model selection<br />
#* Bootstrap/Jacknife<br />
<br />
Each topic will include computational algorithms, problematic aspects such as convergence, biases, main focus will be on Bayesian and maximum likelihood methods.<br />
<br />
== Assignments ==<br />
<br />
This list of assignments is an example, difficulty of assignments will depend on the overall class programming skills. Each assignment topic will be introduced in detail during class. The final set of assignments is not specified yet but it will look similar to the ones shown below:<br />
<br />
# Read and write a tree structure<br />
# Simulate data on a tree<br />
# Simulate data using the coalescent<br />
# Construct an ABC sampler to estimate the effective population size<br />
# Model selection using the program MIGRATE<br />
# Project: The project will discuss either (1) a complex analysis of data or (2) software development or (3) a theory section we did not discuss. The project consists of two parts, a report (of not more than 8 pages) and a presentation of 10 minutes. We will develop ideas for the project during class.<br />
<br />
* Undergraduate students can leave out one of the assignments (1-5).<br />
<br />
== Lecture Schedule ==<br />
<br />
# Introduction. Trees and tree representation (Aug. 29)<br />
# Python and trees (Aug. 31)<br />
# Parsimony (Sep 5)<br />
# Python and parsimony (Sep 7)<br />
# Searching for the best tree(s) (Sep 12)<br />
# Substitution models and distance (Sep 14)<br />
# Substitution models general Sep 19)<br />
# Substitution model exercise Sep 21)<br />
# Rate variation and more substitution models Sep 26)<br />
# Maximum Likelihood (Sep 28)<br />
# Maximum Likelihood (Oct 3)<br />
# Bayesian inference (Oct 5)<br />
# Markov chain Monte Carlo (Oct 10)<br />
# ABC – approximate Bayesian computing (Oct 12)<br />
# The coalescent (Oct 17)<br />
# Coalescent simulation and extensions to the coalescent (Oct 19)<br />
# Gene tree vs Species tree (Oct 24)<br />
# Gene tree vs Species tree (Oct 26)<br />
# Model Selection (Oct 31)<br />
# Bootstrap/Jacknife (Nov 2)<br />
# Review session (Nov 7)<br />
# Mid term (Nov 9)<br />
# Project (Nov 14)<br />
# Project (Nov 16)<br />
# Project (Nov 21)<br />
# Project (Nov 28)<br />
# Project (Nov 30)<br />
# Presentation (Dec 5)<br />
# Presentation (Dec 7)</div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1004ISC-53172017-08-27T22:43:04Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> <p>Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </p></span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br />
<span><p><br />
* [[Syllabus]]<br />
</p></span><br />
<!-- * [[Reading]]<br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]] --></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1003ISC-53172017-08-27T22:42:15Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
<span> Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. </span><br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br />
* [[Syllabus]]<br />
<!-- * [[Reading]]<br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]] --></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=ISC-5317&diff=1002ISC-53172017-08-27T22:35:55Z<p>Peter Beerli: </p>
<hr />
<div>[[File:compevol.png|top|left]]<br />
Advanced computational methods are becoming increasingly important in biology. A wide range of applications — including, for instance, identifying pathogens, tracing viral transmission pathways, and reconstructing the geographic expansion of humans out of Africa — rely on evolutionary inference. This course will cover the methods currently used for evolutionary inference, the stochastic models and inference principles they are based on, and how they are implemented in practice. <br />
<br />
<!-- In a separate lab-session we will learn python and apply it to understand phylogenetic trees and mutation models. --><br />
<br />
* [[Syllabus]]<br />
<!-- * [[Reading]]<br />
* [http://people.sc.fsu.edu/~pbeerli/classes/ISC5317/ISC5317/Lectures.html Lectures]<br />
* [[Lab]]<br />
* [[Heroes]]<br />
* [[Misc]] --></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=UnixRX&diff=1001UnixRX2017-08-26T14:25:32Z<p>Peter Beerli: </p>
<hr />
<div>[[File:unixrx2017_2000px.png|left|top|800px]]<br />
'''Course notes for the Workshop August 2017:<br />
'''<br />
# Thursday: Python lists, loops, how to code a program from start to finish: example "calculate Pi using the Monte Carlo method"<br />
# Friday: Functions, reading and writing, plotting and other packages to make Python life easier<br />
[http://peterbeerli.com/workshops/unixrx/unixrx_2017.zip Workshop codes and presentation] <br />
<br />
[[File:unixrx2017_groupphoto.jpg|center|top|500px]]<br />
<br />
<br />
----<br />
<br />
<br />
<br />
<br />
[[File:unixrx.png|center|top|800px]]<br />
'''Course notes for the Workshop May 2013:<br />
'''<br />
# [[Media:unixrx_1_intro.pdf|Monday: UNIX introduction]]. On the first day, we explore the UNIX command line, learn about copying renaming, deleting, but also about extracting lines from files etc. ([[Media:unixcheatsheet.pdf|UNIX cheat sheet]])<br />
# [[Media:unixrx_2_python.pdf|Tuesday: Python baby steps: calculating Pi]] We learn the very basics of the programming language Python, and end the day with writing a full Python program to estimate the value of Pi using a Monte Carlo approach.<br />
# [[Media:unixrx_3_readwrite.pdf|Wednesday: Reading and Writing]]. We learn how to read from a file and write to a file using python.<br />
# [[Media:unixrx_4_plotting.pdf|Thursday: Plotting]]. Python makes plotting easy and we can create nice XY-plots and histograms.<br />
# [[Media:unixrx_5_scpy_numpy.pdf|Friday: Scipy/Numpy and other complications]]. Python has a small core but there are many modules that can be imported, modules for computation such as Scipy and Numpy are necessary if you want to do any serious computing with python. We learn about how to use these models.<br />
[http://peterbeerli.com/workshops/unixrx/unixrx_2013.zip Workshop codes and presentation] <br />
[[File:groupsmall.jpg|center|bottom|500px]]<br></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=UnixRX&diff=1000UnixRX2017-08-26T14:21:59Z<p>Peter Beerli: </p>
<hr />
<div>[[File:unixrx2017_2000px.png|left|top|800px]]<br />
'''Course notes for the Workshop August 2017:<br />
'''<br />
# Thursday: Python lists, loops, how to code a program from start to finish: example "calculate Pi using the Monte Carlo method"<br />
# Friday: Functions, reading and writing, plotting and other packages to make Python life easier<br />
[http://peterbeerli.com/workshops/unixrx/unixrx_2017.zip Workshop codes and presentation] <br />
<br />
[[File:unixrx2017_groupphoto.jpg|center|top|500px]]<br />
<br />
<br />
----<br />
<br />
<br />
<br />
<br />
[[File:unixrx.png|center|top|800px]]<br />
'''Course notes for the Workshop May 2013:<br />
'''<br />
# [[Media:unixrx_1_intro.pdf|Monday: UNIX introduction]]. On the first day, we explore the UNIX command line, learn about copying renaming, deleting, but also about extracting lines from files etc. ([[Media:unixcheatsheet.pdf|UNIX cheat sheet]])<br />
# [[Media:unixrx_2_python.pdf|Tuesday: Python baby steps: calculating Pi]] We learn the very basics of the programming language Python, and end the day with writing a full Python program to estimate the value of Pi using a Monte Carlo approach.<br />
# [[Media:unixrx_3_readwrite.pdf|Wednesday: Reading and Writing]]. We learn how to read from a file and write to a file using python.<br />
# [[Media:unixrx_4_plotting.pdf|Thursday: Plotting]]. Python makes plotting easy and we can create nice XY-plots and histograms.<br />
# [[Media:unixrx_5_scpy_numpy.pdf|Friday: Scipy/Numpy and other complications]]. Python has a small core but there are many modules that can be imported, modules for computation such as Scipy and Numpy are necessary if you want to do any serious computing with python. We learn about how to use these models.<br />
<br />
[[File:groupsmall.jpg|center|bottom|500px]]<br></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=UnixRX&diff=999UnixRX2017-08-26T14:17:56Z<p>Peter Beerli: </p>
<hr />
<div>[[File:unixrx2017_2000px.png|left|top|800px]]<br />
'''Course notes for the Workshop August 2017:<br />
'''<br />
# Thursday: Python lists, loops, how to code a program from start to finish: example "calculate Pi using the Monet Carlo method"<br />
# Friday: Functions, reading and writing, plotting and other packages to make python life easier<br />
[http://peterbeerli.com/workshops/unixrx/unixrx_2017.zip Workshop codes and presentation] <br />
<br />
[[File:unixrx2017_groupphoto.jpg|center|top|500px]]<br />
<br />
<br />
----<br />
<br />
<br />
<br />
<br />
[[File:unixrx.png|center|top|800px]]<br />
'''Course notes for the Workshop in May 2013:<br />
'''<br />
# [[Media:unixrx_1_intro.pdf|Monday: UNIX introduction]]. On the first day, we explore the UNIX command line, learn about copying renaming, deleting, but also about extracting lines from files etc. ([[Media:unixcheatsheet.pdf|UNIX cheatsheet]])<br />
# [[Media:unixrx_2_python.pdf|Tuesday: Python baby steps: calculating Pi]] We learn the very basics of the programming language Python, and end the day with writing a full python program to estimate the value of Pi using a Monte Carlo approach.<br />
# [[Media:unixrx_3_readwrite.pdf|Wednesday: Reading and Writing]]. We learn how to read from a file and write to a file using python.<br />
# [[Media:unixrx_4_plotting.pdf|Thursday: Plotting]]. Python makes plotting easy and we can create nice xy-plots and histograms.<br />
# [[Media:unixrx_5_scpy_numpy.pdf|Friday: Scipy/Numpy and other complications]]. Python has a small core but there are many modules that can be imported, modules for computation such as scipy and numpy are necessary if you want to do any serious computing with python. We learn about how to use these models.<br />
<br />
[[File:groupsmall.jpg|center|bottom|500px]]<br></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=File:Unixrx2017_groupphoto.jpg&diff=998File:Unixrx2017 groupphoto.jpg2017-08-26T14:14:54Z<p>Peter Beerli: </p>
<hr />
<div></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=UnixRX&diff=997UnixRX2017-08-26T14:14:05Z<p>Peter Beerli: </p>
<hr />
<div>[[File:unixrx2017_2000px.png|left|top|800px]]<br />
'''Course notes for the Workshop August 2017:<br />
'''<br />
# Thursday: Python lists, loops, how to code a program from start to finish: example "calculate Pi using the Monet Carlo method"<br />
# Friday: Functions, reading and writing, plotting and other packages to make python life easier<br />
[http://peterbeerli.com/workshops/unixrx/unixrx_2017.zip Workshop codes and presentation] <br />
<br />
[[File:unixrx2017_groupphoto.jpg|center|top|800px]]<br />
<br />
<br />
----<br />
<br />
<br />
<br />
<br />
[[File:unixrx.png|center|top|800px]]<br />
'''Course notes for the Workshop in May 2013:<br />
'''<br />
# [[Media:unixrx_1_intro.pdf|Monday: UNIX introduction]]. On the first day, we explore the UNIX command line, learn about copying renaming, deleting, but also about extracting lines from files etc. ([[Media:unixcheatsheet.pdf|UNIX cheatsheet]])<br />
# [[Media:unixrx_2_python.pdf|Tuesday: Python baby steps: calculating Pi]] We learn the very basics of the programming language Python, and end the day with writing a full python program to estimate the value of Pi using a Monte Carlo approach.<br />
# [[Media:unixrx_3_readwrite.pdf|Wednesday: Reading and Writing]]. We learn how to read from a file and write to a file using python.<br />
# [[Media:unixrx_4_plotting.pdf|Thursday: Plotting]]. Python makes plotting easy and we can create nice xy-plots and histograms.<br />
# [[Media:unixrx_5_scpy_numpy.pdf|Friday: Scipy/Numpy and other complications]]. Python has a small core but there are many modules that can be imported, modules for computation such as scipy and numpy are necessary if you want to do any serious computing with python. We learn about how to use these models.<br />
<br />
[[File:groupsmall.jpg|center|bottom|500px]]<br></div>Peter Beerlihttp://www.peterbeerli.com/classes/index.php?title=UnixRX&diff=996UnixRX2017-08-25T13:21:03Z<p>Peter Beerli: </p>
<hr />
<div>[[File:unixrx2017_2000px.png|left|top|800px]]<br />
'''Course notes for the Workshop August 2017:<br />
'''<br />
# Thursday: Python lists, loops, how to code a program from start to finish: example "calculate Pi using the Monet Carlo method"<br />
# Friday: Functions, reading and writing, plotting and other packages to make python life easier<br />
[http://peterbeerli.com/workshops/unixrx/unixrx_2017.zip Workshop codes and presentation] <br />
<br />
<br />
<br />
<br />
----<br />
<br />
<br />
<br />
<br />
[[File:unixrx.png|center|top|800px]]<br />
'''Course notes for the Workshop in May 2013:<br />
'''<br />
# [[Media:unixrx_1_intro.pdf|Monday: UNIX introduction]]. On the first day, we explore the UNIX command line, learn about copying renaming, deleting, but also about extracting lines from files etc. ([[Media:unixcheatsheet.pdf|UNIX cheatsheet]])<br />
# [[Media:unixrx_2_python.pdf|Tuesday: Python baby steps: calculating Pi]] We learn the very basics of the programming language Python, and end the day with writing a full python program to estimate the value of Pi using a Monte Carlo approach.<br />
# [[Media:unixrx_3_readwrite.pdf|Wednesday: Reading and Writing]]. We learn how to read from a file and write to a file using python.<br />
# [[Media:unixrx_4_plotting.pdf|Thursday: Plotting]]. Python makes plotting easy and we can create nice xy-plots and histograms.<br />
# [[Media:unixrx_5_scpy_numpy.pdf|Friday: Scipy/Numpy and other complications]]. Python has a small core but there are many modules that can be imported, modules for computation such as scipy and numpy are necessary if you want to do any serious computing with python. We learn about how to use these models.<br />
<br />
[[File:groupsmall.jpg|center|bottom|500px]]<br></div>Peter Beerli