Difference between revisions of "BCH394P BCH364C 2023"

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(Syllabus & course outline)
(Lectures & Handouts)
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== Lectures & Handouts ==
 
== Lectures & Handouts ==
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'''Apr 13 - 20, 2023 - Final Project Presentations'''
 
'''Apr 13 - 20, 2023 - Final Project Presentations'''
 
* Welcome to the end of the course!  You made it!  The last 3 days will be presentations of your class projects.
 
* Welcome to the end of the course!  You made it!  The last 3 days will be presentations of your class projects.
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'''Mar 7, 2023 - Clustering II'''
 
'''Mar 7, 2023 - Clustering II'''
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<!-- * Fun article: [http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2002050 All biology is computational biology]-->
 
<!-- * Fun article: [http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2002050 All biology is computational biology]-->
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* We'll be continuing the slides from just before the guest lecture
 
* We'll be continuing the slides from just before the guest lecture
 
* I'm also posting the next (last) problem set:
 
* I'm also posting the next (last) problem set:
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* [http://www.marcottelab.org/users/BCH394P_364C_2023/1832HumanProteinsPhyloprofiles.txt Human protein phylogenetic profiles]. These data come from [http://www.marcottelab.org/users/BCH394P_364C_2023/CiliaPhyloProfiles.pdf this paper].
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/1832HumanProteinsPhyloprofiles.txt Human protein phylogenetic profiles]. These data come from [http://www.marcottelab.org/users/BCH394P_364C_2023/CiliaPhyloProfiles.pdf this paper].
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/1832HumanProteinsCFMS.txt Human protein co-fractionation/mass spectrometry profiles].  These data come from [http://www.marcottelab.org/paper-pdfs/Nature_AnimalComplexes_2015.pdf this paper].
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/1832HumanProteinsCFMS.txt Human protein co-fractionation/mass spectrometry profiles].  These data come from [http://www.marcottelab.org/paper-pdfs/Nature_AnimalComplexes_2015.pdf this paper].
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<!--* [https://twitter.com/iddux/status/1377587235051204610 New changes for the next version of Python?]-->
 
<!--* [https://twitter.com/iddux/status/1377587235051204610 New changes for the next version of Python?]-->
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<!--
 
Reading:
 
Reading:
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/nature_review_2000.pdf Review of phylogenetic profiles]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/nature_review_2000.pdf Review of phylogenetic profiles]
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* [http://www.marcottelab.org/users/BCH394P_364C_2023/Ecoli_genome.txt E. coli genome]
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/Ecoli_genome.txt E. coli genome]
 
* Python 2 vs 3? Bioinformatics researchers [http://astrofrog.github.io/blog/2015/05/09/2015-survey-results/ held out for 2 until quite recently], but [https://careerkarma.com/blog/python-2-vs-python-3/ the shift to 3 is pretty clear now]. We'll use Python 3 (the latest version is 3.10, but any recent version will be fine), but Rosalind and some materials are only available in Python 2.7, so we'll generally try to be version agnostic for compatibility. Use whichever you wish, but be aware that support for Python 2.7 has officially been stopped. For beginners, the [http://www.practicepython.org/blog/2017/02/09/python2-and-3.html differences are quite minimal] and are [https://www.guru99.com/python-2-vs-python-3.html summarized in a table here].  There's also a great [https://python-future.org/compatible_idioms.html cheat sheet here] for writing code compatible with both versions.
 
* Python 2 vs 3? Bioinformatics researchers [http://astrofrog.github.io/blog/2015/05/09/2015-survey-results/ held out for 2 until quite recently], but [https://careerkarma.com/blog/python-2-vs-python-3/ the shift to 3 is pretty clear now]. We'll use Python 3 (the latest version is 3.10, but any recent version will be fine), but Rosalind and some materials are only available in Python 2.7, so we'll generally try to be version agnostic for compatibility. Use whichever you wish, but be aware that support for Python 2.7 has officially been stopped. For beginners, the [http://www.practicepython.org/blog/2017/02/09/python2-and-3.html differences are quite minimal] and are [https://www.guru99.com/python-2-vs-python-3.html summarized in a table here].  There's also a great [https://python-future.org/compatible_idioms.html cheat sheet here] for writing code compatible with both versions.
 
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'''Jan 10, 2023 - Introduction'''
 
'''Jan 10, 2023 - Introduction'''
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/BCH394P-364C-IntroAndRosalind-Spring2023.pdf Today's slides]<br>
 
* [http://www.marcottelab.org/users/BCH394P_364C_2023/BCH394P-364C-IntroAndRosalind-Spring2023.pdf Today's slides]<br>
* We'll be conducting homework using the online environment [http://rosalind.info/faq/ Rosalind].  Go ahead and register on the site, and enroll specifically for BCH394P/364C (Spring 2023) Systems Biology/Bioinformatics using [https://rosalind.info/classes/enroll/3862a679ae/ ''this link''].  Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is '''due by 11:59PM January 27'''.
+
* We'll be conducting homework using the online environment [http://rosalind.info/faq/ Rosalind].  Go ahead and register on the site, and enroll specifically for BCH394P/364C (Spring 2023) Systems Biology/Bioinformatics using [https://rosalind.info/classes/enroll/fb013a1910/ ''this link''].  Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is '''due by 10:00PM January 18'''.
 
Here are some online Python resources that you might find useful:
 
Here are some online Python resources that you might find useful:
 
* First and foremost, and very, very useful if you're a complete Python newbie:  Eric Matthes's [https://nostarch.com/pythoncrashcourse2e Python Crash Course book]. He made some GREAT, free [https://github.com/ehmatthes/pcc/releases/download/v1.0.0/beginners_python_cheat_sheet_pcc_all.pdf Python command cheat sheets] to support the book.
 
* First and foremost, and very, very useful if you're a complete Python newbie:  Eric Matthes's [https://nostarch.com/pythoncrashcourse2e Python Crash Course book]. He made some GREAT, free [https://github.com/ehmatthes/pcc/releases/download/v1.0.0/beginners_python_cheat_sheet_pcc_all.pdf Python command cheat sheets] to support the book.
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* If you have any basic experience at all in other programming languages, Google offered an extremely good, 2 day intro course to Python (albeit version 2) that is now [https://www.youtube.com/playlist?list=PLC8825D0450647509 available on Youtube].
 
* If you have any basic experience at all in other programming languages, Google offered an extremely good, 2 day intro course to Python (albeit version 2) that is now [https://www.youtube.com/playlist?list=PLC8825D0450647509 available on Youtube].
 
* Khan Academy has archived their older intro videos on Python [https://www.youtube.com/user/khanacademy/search?query=python here]<br>
 
* Khan Academy has archived their older intro videos on Python [https://www.youtube.com/user/khanacademy/search?query=python here]<br>
 
  
 
== Syllabus & course outline ==
 
== Syllabus & course outline ==

Revision as of 20:07, 7 January 2023

BCH394P/BCH364C Systems Biology & Bioinformatics

Course unique #: 55425/55330
Lectures: Tues/Thurs 11 – 12:30 PM WEL 2.110
Instructor: Edward Marcotte, marcotte @ utexas.edu

  • Office hours: Mon 4 – 5 PM on the class Zoom channel (available on Canvas)

TA: Matt McGuffie, mmcguffie @ utexas.edu

  • TA Office hours: Wed 3 - 4 PM / Thu 12:30 - 1:30 in MBB 1.448BA or by appointment on Zoom

Class Canvas site: https://utexas.instructure.com/courses/1352289

Lectures & Handouts

Jan 10, 2023 - Introduction

  • Today's slides
  • We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site, and enroll specifically for BCH394P/364C (Spring 2023) Systems Biology/Bioinformatics using this link. Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is due by 10:00PM January 18.

Here are some online Python resources that you might find useful:

  • First and foremost, and very, very useful if you're a complete Python newbie: Eric Matthes's Python Crash Course book. He made some GREAT, free Python command cheat sheets to support the book.
  • Practical Python, worth checking out!
  • If you have any basic experience at all in other programming languages, Google offered an extremely good, 2 day intro course to Python (albeit version 2) that is now available on Youtube.
  • Khan Academy has archived their older intro videos on Python here

Syllabus & course outline

Course syllabus

An introduction to systems biology and bioinformatics, emphasizing quantitative analysis of high-throughput biological data, and covering typical data, data analysis, and computer algorithms. Topics will include introductory probability and statistics, basics of Python programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, proteomics, synthetic biology, analysis of large-scale gene expression data, data clustering, biological pattern recognition, and gene and protein networks.

Open to graduate students and upper division undergrads (with permission) in natural sciences and engineering. Prerequisites: Basic familiarity with molecular biology, statistics & computing, but realistically, it is expected that students will have extremely varied backgrounds. Undergraduates have additional prerequisites, as listed in the catalog.

Note that this is not a course on practical sequence analysis or using web-based tools. Although we will use a number of these to help illustrate points, the focus of the course will be on learning the underlying algorithms, exploratory data analyses, and their applications, esp. in high-throughput biology. By the end of the course, students will know the fundamentals of important algorithms in bioinformatics and systems biology, will be able to design and implement computational studies in biology, and will have performed an element of original computational biology research.

Most of the lectures will be from research articles and slides posted online, with some material from the...
Optional text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),

For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is very good. A reasonable online resource for beginners is Statistics Done Wrong.

Some online references:
An online bioinformatics course
Online probability & stats texts: #1, #2 (which has some lovely visualizations)

No exams will be given. Grades will be based on online homework (counting 30% of the grade), 3 problem sets (given every 2-3 weeks and counting 15% each towards the final grade) and an independent course project (25% of final grade), which can be collaborative (1-3 students/project). The course project will consist of a research project on a bioinformatics topic chosen by the student (with approval by the instructor) containing an element of independent computational biology research (e.g. calculation, programming, database analysis, etc.). This will be turned in as a link to a web page. The final project is due by 10 PM, April 12, 2023. The last 3 classes will be spent presenting your projects to each other. (The presentation will account for 5/25 points of the project grade.)

If at some point, we have to go into coronavirus lockdown, that portion of the class will be web-based. We will hold lectures by Zoom during the normally scheduled class time. Log in to the UT Canvas class page for the link, or, if you are auditing, email the TA and we will send the link by return email. Slides will be posted before class so you can follow along with the material. We'll record the lectures & post the recordings afterward on Canvas so any of you who might be in other time zones or otherwise be unable to make class will have the opportunity to watch them. Note that the recordings will only be available on Canvas and are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form. Violation of this restriction could lead to Student Misconduct proceedings.

Online homework will be assigned and evaluated using the free bioinformatics web resource Rosalind.

All projects and homework will be turned in electronically and time-stamped. No makeup work will be given. Instead, all students have 5 days of free “late time” (for the entire semester, NOT per project, and counting weekends/holidays). For projects turned in late, days will be deducted from the 5 day total (or what remains of it) by the number of days late (in 1 day increments, rounding up, i.e. 10 minutes late = 1 day deducted). Once the full 5 days have been used up, assignments will be penalized 10 percent per day late (rounding up), i.e., a 50 point assignment turned in 1.5 days late would be penalized 20%, or 10 points.

Homework, problem sets, and the project total to a possible 100 points. There will be no curving of grades, nor will grades be rounded up. We’ll use the plus/minus grading system, so: A= 92 and above, A-=90 to 91.99, etc. Just for clarity's sake, here are the cutoffs for the grades: 92% = A, 90% = A- < 92%, 88% = B+ < 90%, 82% = B < 88%, 80% = B- < 82%, 78% = C+ < 80%, 72% = C < 78%, 70% = C- < 72%, 68% = D+ < 70%, 62% = D < 68%, 60% = D- < 62%, F < 60%.

Students are welcome to discuss ideas and problems with each other, but all programs, Rosalind homework, problem sets, and written solutions should be performed independently (except the final collaborative project). Students are expected to follow the UT honor code. Cheating, plagiarism, copying, & reuse of prior homework, projects, or programs from CourseHero, Github, or any other sources are all strictly forbidden and constitute breaches of academic integrity and cause for dismissal with a failing grade, possibly expulsion (UT's academic integrity policy). In particular, no materials used in this class, including, but not limited to, lecture hand-outs, videos, assessments (papers, projects, homework assignments), in-class materials, review sheets, and additional problem sets, may be shared online or with anyone outside of the class unless you have the instructor’s explicit, written permission. Any materials found online (e.g. in CourseHero) that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.

The final project web site is due by 10 PM April 12, 2023.