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'''[https://docs.google.com/spreadsheet/ccc?key=0Ar2M8lIkl9T5dDN4d1Q0aDBGcThXdjV2c21ESWVxSGc Class Schedule]''' (including a list of topics and quiz dates) | '''[https://docs.google.com/spreadsheet/ccc?key=0Ar2M8lIkl9T5dDN4d1Q0aDBGcThXdjV2c21ESWVxSGc Class Schedule]''' (including a list of topics and quiz dates) | ||
- | '''[https://docs.google.com/spreadsheet/viewform?formkey=dGprVkplZng1WUxZOXJTdWppN19yUHc6MQ Poll]''' with 3 Qs on difficulty of classes 1 to 4 (to be filled out by 25-Jan. | + | '''[https://docs.google.com/spreadsheet/viewform?formkey=dGprVkplZng1WUxZOXJTdWppN19yUHc6MQ Poll]''' with 3 Qs on difficulty of classes 1 to 4 (to be filled out by 25-Jan.) |
==Discussion Section Readings== | ==Discussion Section Readings== |
Revision as of 12:12, 21 January 2012
Contents |
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=21914&term=201201 , viz:
MB&B 452 01 (21914) /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 Spring 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 written project.
MB&B752/MCDB752
This version of the course consists of lectures, written problem sets, and a final, graduate level written 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 753b3, Bioinformatics: Practical Application of Data Mining (1st half of term)
MB&B 754b4, 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 9 Jan.)
Discussion section: Wed 6-7 pm in Gibbs 263 (starting Jan 18)
Poll for students to indicate good times for the weekly discussion section
Instructors
Instructor-in-Charge
Name | Office | |
---|---|---|
Mark Gerstein | Bass 432A | mark.gerstein(at)yale.edu |
Guest Instructors
Name | Office | |
---|---|---|
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 |
Teaching Fellows
Name | Office | |
---|---|---|
Lucas Lochovsky | Bass 437 | lucas.lochovsky(at)yale.edu |
Jane Leng | Bass 437 | jing.leng(at)yale.edu |
Alice Zhou (select lectures) | Mason Laboratory | alice.zhou(at)yale.edu |
Topics/Class Schedule
Class Schedule (including a list of topics and quiz dates)
Poll with 3 Qs on difficulty of classes 1 to 4 (to be filled out by 25-Jan.)
Discussion Section Readings
Session 1
Metzker ML. "Sequencing technologies - the next generation” Nature Reviews Genetics. 11 (2010) PDF
Wheeler DA et al. "The complete genome of an individual by massively parallel DNA sequencing,” Nature. 452:872-876 (2008) PDF
Session 2
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 3
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 4
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
Garnier J, Gibrat JF, Robson B. (1996) GOR method for predicting protein secondary structure from amino acid sequence.Methods in Enzymology,266: 540-53. PMID: 8743705. 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
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 7
Perelson AS. Modelling viral and immune system dynamics. Nat Rev Immunol. 2002 Jan;2(1):28-36. PDF
Session 8
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 9
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
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)
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.
Non-CBB Final Project
[tbd]
CBB Final Project
[tbd]
Grade Categories
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
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
2011, 2010, 2009 and earlier (Pointers on finding things on old class pages)