Cbb752b12
From GersteinInfo
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==Topics/Class Schedule== | ==Topics/Class Schedule== | ||
| - | [https:// | + | [https://docs.google.com/spreadsheet/ccc?key=0Ar2M8lIkl9T5dDN4d1Q0aDBGcThXdjV2c21ESWVxSGc Class Schedule] (including a list of topics and quiz dates) |
==Discussion Sections== | ==Discussion Sections== | ||
Revision as of 04:16, 20 December 2011
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/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.
Quizzes and Final Project
There will be approximately four short quizzes during the semester and a take-home final project. For CBB and CS sections, the final project will be a programming assignment. For MB&B, the final project will be a paper. Further details will be announced at a later date.
Literature discussion section
One session of 60 minutes per week, time to be arranged. Student presentations of recent research papers relevant to the topics of the course. Led by Lucas Lochovsky (Bass, Rm 437; (203) 432-5405; lucas.lochovsky(at)yale.edu) and Jane Leng (Bass, Rm 437; (203) 432-5405; jing.leng(at)yale.edu).
Programming Projects/Problem Sets
Students taking this course listed under Computational Biology and Bioinformatics or Computer Science will be required to complete several short programming assignments. Further details will be discussed in the literature discussion section and during class.
Grade Categories
CBB and CPSC Sections:
| Category | % of Total Grade |
|---|---|
| Quizzes | 33.25% |
| Final Project | 33.25% |
| Discussion Section | 8.50% |
| Programming Assignments | 25.00% |
MBB and MCDB Sections:
| Category | % of Total Grade |
|---|---|
| Quizzes | 33.25% |
| Final Project | 33.25% |
| Discussion Section | 16.75% |
| Problem Sets | 16.75% |
Differences Between Class Sections
In general, the graduate level CS/CBB course is significantly different than MBB/MCDB (graduate and undergraduate) in several ways. Although the lectures are the same for each section, the graduate level CPSC/CBB course has additional programming assignments in addition to the work being completed by the MBB students. Homework for the MBB section centers on the completion of several problem sets without a programming component. The CPSC/CBB section forgoes these problem sets and instead requires that students implement several of the algorithms discussed in class. Also, the final project for CPSC/CBB MUST be a programming assignment rather than the final paper required for the MBB section. Due to the distinct course requirements, category weightings for final grades are also different.
Timing & location
Class: Meeting from 1:00-2:15 pm on Monday and Wednesday, in 305 BASS. (First meeting will be on 9 Jan.)
Discussion section: TBA
Instructors
Instructor-in-Charge
| Name | Office | Office Phone | |
|---|---|---|---|
| Mark Gerstein | Bass 432A | (203) 432-6105 | mark.gerstein(at)yale.edu |
Instructors
| Name | Office | Office Hours | |
|---|---|---|---|
| Corey O'Hern | Mason Laboratory | corey.ohern(at)yale.edu | M 2:15-3:15 PM |
Others to be listed
Teaching Fellows
| Name | Office | Office Phone | |
|---|---|---|---|
| Lucas Lochovsky | Bass Rm 437 | (203) 432-5405 | lucas.lochovsky(at)yale.edu |
| Jane Leng | Bass Rm 437 | (203) 432-5405 | jing.leng(at)yale.edu |
Topics/Class Schedule
Class Schedule (including a list of topics and quiz dates)
Discussion Sections
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 (208) 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
Laura J. van 't Veer et al. Gene expression profiling predicts clinical outcome of breast cancer Nature 415, 530-536 (31 January 2002) | doi:10.1038/415530a; Received 24 August 2001; Accepted 22 November 2001 TEXT
Kwang-Il Goh, Michael E. Cusick, David Vall, Barton Child, Marc Vidal, and Albert-La ́szlo ́ Barabasi (2007) The human disease network Proc Natl Acad Sci U S A. 2007 May 22;104(21):8685-90. Epub 2007 May 14. 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
Non-CBB Final Project
[tbd]
CBB Final Project
[tbd]
Class Requirements
Discussion Section / Readings
Papers will be assigned throughout the course. These papers will be presented and discussed in weekly sections with the TAs. A brief summary (a half-page per article) should be submitted at the beginning of the discussion session.
Bioinformatics quizzes
There will be approximately three 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.
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."
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
Pages from previous years
Research Opportunities
If you're really motivated, take a look at http://bioinfo.mbb.yale.edu/jobs/.
