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CBB 752

Course Information

Course Description

Bioinformatics encompasses the analysis of gene sequences, macromolecular structures, and functional genomics data on a large scale. It represents a major practical application for modern techniques in data mining and simulation. Specific topics to be covered include sequence alignment, large-scale processing, next-generation sequencing data, comparative genomics, phylogenetics, biological database design, geometric analysis of protein structure, molecular-dynamics simulation, biological networks, normalization of microarray data, mining of functional genomics data sets, and machine learning approaches for data integration.

Concise undergraduate course description

Techniques in data mining and simulation applied to bioinformatics, the computational analysis of gene sequences, macromolecular structures, and functional genomics data on a large scale. Sequence alignment, comparative genomics and phylogenetics, biological databases, geometric analysis of protein structure, molecular-dynamics simulation, biological networks, microarray normalization, and machine-learning approaches to data integration.

See entry from undergraduate catalog: http://students.yale.edu/oci/resultDetail.jsp?course=11937&term=201203 , viz:

MB&B 452 01 (11937) /MCDB452/MB&B752/MB&B753/MB&B754/CB&B752/MCDB752/CPSC752
Bioinformatics: Practical Application of Simulation and Data Mining 
Mark Gerstein
MW 1.00-2.15 BASS 305
Fall 2012 
No regular final examination
Areas Sc
Prerequisites: MB&B 301b and MATH 115a or b, or permission of instructor.
MCDB 120a or 200b is a prerequisite for courses numbered MCDB 202 and above.

Different headings for this class

MB&B452/MCDB452

This version of the course consists of lectures, written problem sets, and a final (semi-computational section and a literature survey) project.

MB&B752/MCDB752

This version of the course consists of lectures, written problem sets, and a final (semi-computational section and a literature survey) project.

CB&B752/CPSC752

This version of the course consists of lectures, programming assignments, and a final programming project.


For graduate students the course is broken up into two "modules" (each counting 0.5 credit towards MB&B course requirement):

MB&B 753a3, Bioinformatics: Practical Application of Data Mining (1st half of term)

MB&B 754a4, Bioinformatics: Practical Application of Simulation (2nd half of term)

Each module consists of lectures, written problem sets, and a final, graduate level written project that is half the length of the full course's final project.


For the grade weighting schemes of each course version, see Class Requirements section.

Prerequisites

The course is keyed towards CBB graduate students as well as advanced MB&B undergraduates and graduate students wishing to learn about types of large-scale quantitative analyses that whole-genome sequencing will make possible. It would also be suitable for students from other fields such as computer science or physics wanting to learn about an important new biological application for computation.

Students should have:

A basic knowledge of biochemistry and molecular biology. A knowledge of basic quantitative concepts, such as single variable calculus, some probability and statistics, and basic programming skills. These can be fulfilled by the following prerequisites statement: "Prerequisites: MBB 200 and Mathematics 115 or permission of the instructor."

Timing & location

Class: Meeting from 1:00-2:15 pm on Monday and Wednesday, in Bass 305. (First meeting will be on 29 Aug 2012 (Wed) and the next meeting will be 31 Aug 2012 (Fri).)

Discussion section: wait for further notice.

Instructors

Consultation is available UPON REQUEST or as stipulated by instructors.

Instructor-in-Charge

Name Office Email
Mark Gerstein Bass 432A mark.gerstein(at)yale.edu

Guest Instructors

Name Office Email
Corey O'Hern Mason Laboratory corey.ohern(at)yale.edu
Jesse Rinehart 300 George St jesse.rinehart(at)yale.edu
James Noonan 333 Cedar St james.noonan(at)yale.edu
Kei Cheung 300 George St kei.cheung(at)yale.edu
Steven Kleinstein 300 George St steven.kleinstein(at)yale.edu
Dov Greenbaum -- dov.greenbaum(at)aya.yale.edu

Teaching Fellows

Name Office Email
Jieming Chen Bass 437, Bass 323 jieming.chen(at)yale.edu
Yao Fu Bass 437 yao.fu(at)yale.edu
Wendell Smith (selected lectures) Mason Laboratory 313 wendell.smith(at)yale.edu

Topics/Class Schedule

Class Schedule (including a list of topics and quiz dates)

Polls

Poll for students' sign up and good times for the weekly discussion section Result

Discussion Section Readings

Session 1

T.F. Smith and M.S. Waterman. (1981) Identification of common molecular subsequences. Journal of Molecular Biology,147(1): 195-7. PMID: 7265238. PDF

Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. (1990) Basic local alignment search tool. Journal of Molecular Biology, 215(3):403-10. PMID: 2231712. PDF

Session 2

Metzker ML. "Sequencing technologies - the next generation” Nature Reviews Genetics. 11 (2010) PDF

Bailey TL, Williams N, Misleh C, Li WW. (2006) MEME: discovering and analyzing DNA and protein sequence motifs, Nucl Acids Res.34:W369-373 PDF

Session 3

Olsen JV, Blagoev B, Gnad F, Macek B, Kumar C, Mortensen P, Mann M. (2006) Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.Cell. 2006 Nov 3;127(3):635-48. PDF

Nevan J. Krogan et al (2006) Global landscape of protein complexes in the yeast Saccharomyces cerevisiae Nature 440, 637-643 (30 March 2006) PDF

Session 4

Wheeler DA et al. "The complete genome of an individual by massively parallel DNA sequencing,” Nature. 452:872-876 (2008) PDF

Antezana E, Egaña M, Blondé W, Illarramendi A, Bilbao I, De Baets B, Stevens R, Mironov V, Kuiper M. (2009) The Cell Cycle Ontology: an application ontology for the representation and integrated analysis of the cell cycle process. Genome Biol. 2009;10(5):R58. Epub 2009 May 29. PDF

Session 5

Sotiriou et al. (2006) Gene Expression Profiling in Breast Cancer: Understanding the Molecular Basis of Histologic Grade To Improve Prognosis. JNCI J Natl Cancer Inst (15 February 2006) 98 (4):262-272.doi: 10.1093/jnci/djj052 PDF

Ekman D, Light S, Björklund AK, Elofsson A. (2006) What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae? Genome Biol. 2006;7(6):R45. PDF

Session 6

TBD

Session 7

ML Connolly. (1983) Solvent-accessible surfaces of proteins and nucleic acids. Science, 221(4612): 709-13. PMID: 6879170.PDF

Martin Karplus and J. Andrew McCammon. (2002) Molecular dynamics simulations of biomolecules. Nature Structural Biology,9, 646-52. PMID: 12198485.PDF

Session 8

Dill KA, Ozkan SB, Shell MS, Weikl TR. (2008) The Protein Folding Problem.Annu Rev Biophys,9, 37:289-316. PMID: 2443096.PDF

Bowman GR, Beauchamp KA, Boxer G, Pande VS. “Progress and challenges in the automated construction of Markov state models for full protein systems,” J. Chem. Phys. 131 (2009) 124101 PDF

Session 9

Perelson AS. Modelling viral and immune system dynamics. Nat Rev Immunol. 2002 Jan;2(1):28-36. PDF

Class Requirements

Discussion Section / Readings

Papers will be assigned throughout the course. These papers will be presented and discussed in weekly 60-minute sections with the TFs. A brief summary (a half-page per article) should be submitted at the beginning of the discussion session.

Bioinformatics quizzes

There will be four short quizzes (25 minutes) in class comprising SIMPLE questions that you should be able to answer from the lectures plus the main readings.

Programming Assignments (CBB and CS) and Programming issues

There will be several short programming assignments required for CBB and CS students taking this course. Acceptable languages and submission requirements will be discussed prior to the first assignment. These assignments are NOT required for students not taking the CBB or CS sections of the course.

These are the programming languages that we permit in the programming assignments and final project: Perl, Python, C, C++, MATLAB and R. If you really feel more comfortable with other languages, please email the TFs to discuss. Also, packages such as BioPerl and BioPython are not allowed in the assignments and final project. If in doubt, please consult the TFs.

We recommend the use of PERL for most of the programming. A useful resource is the following book: Programming Perl, 3rd Edition in the O' Reilly series, by Larry Wall, Tom Christiansen, Jon Orwant. The Yale Library has also older editions, which would work too. We would also recommend the following online resources: http://www.perlmonks.org/ and http://stackoverflow.com/. Otherwise, Google is your best friend.

Assignment postings

TBD

Final Project

TBD

Grade Categories


The following are the approximate grading systems:

CBB and CPSC Sections:

Category  % of Total Grade
Quizzes 33%
Final Project 33%
Discussion Section 9%
Programming Assignments 25%

MBB and MCDB Sections:

Category  % of Total Grade
Quizzes 33%
Final Project 33%
Discussion Section 17%
Problem Sets 17%

Relevant Yale College Regulations

Students may have questions concerning end-of-term matters. Links to further information about these regulations can be found below:

http://yalecollege.yale.edu/content/reading-period-and-final-examination-period

http://yalecollege.yale.edu/content/completion-course-work

Brief presentation on how to cite correctly : http://archive.gersteinlab.org/mark/out/log/2012/06.12/cbb752b12/cbb752_cite.ppt

Misc

Permissions on using website material

Graphic for course homepage

If you're really motivated, take a look at http://gersteinlab.org/jobs for further Research Opportunities

Pages from previous years

2012 spring, 2011, 2010, 2009 and earlier (Pointers on finding things on old class pages)

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