Courses:

Foundations of Computational and Systems Biology >> Content Detail



Study Materials



Readings

Amazon logo Help support MIT OpenCourseWare by shopping at Amazon.com! MIT OpenCourseWare offers direct links to Amazon.com to purchase the books cited in this course. Click on the Amazon logo to the left of any citation and purchase the book from Amazon.com, and MIT OpenCourseWare will receive up to 10% of all purchases you make. Your support will enable MIT to continue offering open access to MIT courses.

Amazon logo Mount, David W. Bioinformatics: Sequence and Genome Analysis. Cold Spring Harbor, NY: Cold Spring Harbor Laboratory Press, 2001. ISBN: 9780879695972.
 
LEC #TOPICSREADINGS
1Introduction/Sequence Comparison and Dynamic ProgrammingMount. pp. 1-7, 29-35, 45-48, 51-64.
2Multiple Sequence Alignments IMount. pp. 8-9, 65-89, 96-115, 140-155, 161-170.
3Multiple Sequence Alignments IIMount. pp. 139-150, 152-157, 161-171, 185-198.
4Phylogenetic AnalysisMount. pp. 237-280, 283-286, 291-308.
5Literature DiscussionPellegrini, M., E. M. Marcotte, M. J. Thompson, D. Eisenberg, and T. O. Yeates. "Assigning Protein Functions by Comparative Genome Analysis: Protein Phylogenetic Profiles." Proc. Natl. Acad. Sci. USA. 96, no. 8 (13 Apr 1999): 4285-8.

Suel, G. M., S. W. Lockless, M. A. Wall, and R. Ranganathan. "Evolutionarily Conserved Networks of Residues Mediate Allosteric Communication in Proteins." Nat. Struct. Biol. 10, no. 1 (Jan 2003): 59-69.
6Genome Sequencing and DNA Sequence AnalysisWoolf, Peter, Christopher Burge, Amy Keating, and Michael Yaffe. "Statistics and Probabilty Primer for Computational Biologists." MIT. BE.490/7.91 Spring 2004. (PDF)

Bork, Peer, and Richard Copley. "Genome Speak." Nature 409 (15 Feb 2001): 815.
7DNA Sequence Comparison and AlignmentMount. Chap. 7.
8DNA Motif Modeling and DiscoveryMount. Chap. 4.
9Markov and Hidden Markov Models for DNA SequencesMount. Chap. 4.
10DNA Sequence EvolutionMount. Chap. 4.
11RNA Secondary Structure PredictionMount. Chap. 4.
12Literature Discussion on Predicting the Functions of DNA/RNA SequencesKellis, M., N. Patterson, M. Endrizzi, B. Birren, and E. S. Lander. "Sequencing and Comparison of Yeast Species to Identify Genes and Regulatory Elements." Nature 423, no. 6937 (15 May 2003): 241-54.

Rivas, E., R. J. Klein, T. A. Jones, and S. R. Eddy. "Computational Identification of Noncoding RNAs in E. Coli by Comparative Genomics." Curr. Biol. 11, no. 17 (4 Sep 2001): 1369-73.
13Midterm Exam – in class – Protein and DNA Sequence Analysis
14Protein Secondary Structure Prediction
15Introduction to Protein Structure and Classification
16Comparing Protein Structures

Molecular Modeling: Methods and Applications
17Using Computational Methods to Analyze, Predict, and Design Protein Sequences and Structures

Solving Structures using X-ray Crystallographpy and NMR
Marti-Renom, et. al. Annu. Rev. Biophys. Biomol. Struct. 29 (2000): 291-325.
18Solving Structures using X-ray Crystallographpy and NMR (cont.)

Homology Modeling
Marti-Renom, et. al. Annu. Rev. Biophys. Biomol. Struct. 29 (2000): 291-325.
19Methods for Protein Structure Prediction: Homology Modeling and Fold RecognitionBonneau, and Baker. Annu. Rev. Biophys. Biomol. Struct. 30 (2001): 173-189.
20Threading and ab initio Structure Prediction

Computational Protein Design
21Introduction to Systems BiologyIdeker, and Lauffenburger. TRENDS in Biotechnology 21 (2003): 255-262.
22Feedback Systems and Coupled Differential Equations
23DNA Microarrays and Clustering
24Literature Discussion on DNA Microarrays and ClusteringSegal, E., et. al. "Module Networks: Identifying Regulatory Modules and their Condition-specific Regulators from Gene Expression Data." Nature Genetics (2003). 

Beer, M., and S. Tavazoie. "Predicting Gene expression from Sequence." Cell (2004). 

Background Reading

Friedman, N. "Inferring Cellular Networks Using Probabilistic Graphical Models." Science (2004).

Appendix of Probability and Statistics Primer.
25Computational Annotation of the Proteome
26Literature Discussion on Computational Annotation of the ProteomeBader, J. S., A. Chaudhuri, J. M. Rothberg, and J. Chant. "Gaining Confidence in High-throughput Protein Interaction Networks." Nat Biotechnol. 22, no. 1 (Jan 2004): 78-85. Epub (14 Dec 2003).

Jansen, R., H. Yu, D. Greenbaum, Y. Kluger, N. J. Krogan, S. Chung, A. Emili, M. Snyder, J. F. Greenblatt, and M. Gerstein. "A Bayesian Networks Approach for Predicting Protein-Protein Interactions from Genomic Data." Science 302, no. 5644 (17 Oct 2003): 449-53.

 








© 2017 CourseTube.com, by Higher Ed Media LLC. All Rights Reserved.