The table below maps the readings to specific lecture sessions. In addition, given below the table is a list of references for the course.
Papers
| ses # | TOPICS | Readings |
|---|---|---|
| 1 |
Introduction Course Introduction, Review of Modern Biology I Abstraction Level 1: Sequence |
Course Introduction, Review of Modern Biology I Alterovitz, G., E. Afkhami, and M. Ramoni. “Robotics, Automation, and Statistical Learning for Proteomics.” In Focus on Robotics and Intelligent Systems Research. Edited by F. Columbus. Vol. 1. New York: Nova Science Publishers, Inc., 2005, sections I-II. (In press) Introduction to Bioinformatics Laboratory / Bioinformatics in the Computer Industry Moormans, M. W. Matlab on Athena, Technical Publication AC-71. Cambridge, MA: Massachusetts Institute of Technology, 2001. Pochet, N., et al. “Systematic benchmarking of microarray data classification: assessing the role of nonlinearity and dimensionality reduction.” Bioinformatics, 2004. Kasturi, J., R. Acharya, and M. Ramanathan. “An information theoretic approach for analyzing temporal patterns of gene expression.” Bioinformatics 19, no. 4 (2003): 449-58. |
| 2 |
Abstraction Level 1: Sequence Review of Modern Biology II Sequence Analysis: Motif and Regulation |
Review of Modern Biology II Alterovitz, G., E. Afkhami, and M. Ramoni. “Robotics, Automation, and Statistical Learning for Proteomics.” In Focus on Robotics and Intelligent Systems Research. Edited by F. Columbus. Vol. 1. New York: Nova Science Publishers, Inc., 2005, sections I-II. (In press) Sequence Analysis: Motif and Regulation Kellis, M., et al. “Sequencing and comparison of yeast species to identify genes and regulatory elements.” Nature 423, no. 6937 (2003): 241-54. Kellis, M., et al. “Methods in comparative genomics: genome correspondence, gene identification and regulatory motif discovery.” Journal of Computational Biology 11, no. 2-3 (2004): 319-55. |
| 3 |
Abstraction Level 1: Sequence Sequence Analysis: Genes and Genome Sequence Analysis: Gene Evolution |
Sequence Analysis: Genes and Genome Kellis, M., B. W. Birren, and E. S. Lander. “Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae.” Nature 428, no. 6983 (2004): 617-24. Jaillon, O., et al. “Genome duplication in the teleost fish Tetraodon nigroviridis reveals the early vertebrate proto-karyotype. Nature 431, no. 7011 (2004): 946-57. Sequence Analysis: Gene Evolution Kellis, M., B. W. Birren, and E. S. Lander. “Proof and evolutionary analysis of ancient genome duplication in the yeast Saccharomyces cerevisiae.” Nature 428, no. 6983 (2004): 617-24. |
| 4 |
Abstraction Level 2: Expression Machine Learning: Bayesian Methodologies |
Microarray Expression Data Analysis Machine Learning: Bayesian Methodologies Ramoni, M.F., P. Sebastiani, and I.S. Kohane. “Cluster analysis of gene expression dynamics.” Proc Natl Acad Sci U S A 99, no. 14 (2002): 9121-6. |
| 5 |
Abstraction Level 2: Expression Bioinformatics in the Biotech Industry Abstraction Level 4: Systems/Misc Control and Feedback in Systems |
Bioinformatics in the Biotech Industry Kramer, R., and D. Cohen. “Functional genomics to new drug targets.” Nature Reviews Drug Discovery 3, no. 11 (2004): 965-72. Lawler, A. “Diabetes research. Broad-Novartis venture promises a no-strings, public gene database.” Science 306, no. 5697 (2004): 795. Control and Feedback in Systems Rangel, C., et al. “Modeling T-cell activation using gene expression profiling and state-space models.” Bioinformatics 20, no. 9 (2004): 1361-72. |
| 6 |
Abstraction Level 4: Systems/Misc Scale-free Networks I Scale-free Networks II |
Scale-free Networks I Goh, K. I., et al. “Classification of scale-free networks.” Proc Natl Acad Sci U S A 99, no. 20 (2002): 12583-8. Bilke, S., and C. Peterson. “Topological properties of citation and metabolic networks.” Phys Rev E Stat Nonlin Soft Matter Phys 64, no. 3 Pt 2 (2001): 036106. Scale-free Networks II Goh, K. I., et al. “Classification of scale-free networks.” Proc Natl Acad Sci U S A 99, no. 20 (2002): 12583-8. Rzhetsky, A., and S. M. Gomez. “Birth of scale-free molecular networks and the number of distinct DNA and protein domains pergenome.” Bioinformatics 17, no. 10 (2001): 988-96. |
| 7 |
Abstraction Level 3: Proteomics Statistical Models and Stochastic Processes in Proteomics Signal Processing for Proteomics |
Statistical Models and Stochastic Processes in Proteomics Alterovitz, G., E. Afkhami, and M. Ramoni. “Robotics, Automation, and Statistical Learning for Proteomics.” In Focus on Robotics and Intelligent Systems Research. Edited by F. Columbus. Vol. 1. New York: Nova Science Publishers, Inc., 2005, sections IV-V. (In press) Signal Processing for Proteomics Baggerly, K. A., J. S. Morris, and K. R. Coombes. “Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments.” Bioinformatics 20, no. 5 (2004): 777-85. |
| 8 |
Abstraction Level 3: Proteomics Conclusion Project Discussion and Wrap-up |
Biological Methods, Automation, Robotics Alterovitz, G., E. Afkhami, and M. Ramoni. “Robotics, Automation, and Statistical Learning for Proteomics.” In Focus on Robotics and Intelligent Systems Research. Edited by F. Columbus. Vol. 1. New York: Nova Science Publishers, Inc., 2005, section III. (In press) |
References
Book Chapter
Alterovitz, G., E. Afkhami, and M. Ramoni. “Robotics, Automation, and Statistical Learning for Proteomics.” In Focus on Robotics and Intelligent Systems Research. Edited by F. Columbus. Vol. 1. New York: Nova Science Publishers, Inc., 2005. (In press).
Texts
Oppenheim, A. V., A. S. Willsky, and H. Nawab. Signals and Systems. 3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1997. ISBN: 0138147574.
Papoulis, A., and S. U. Pillai. Probability, Random Variables and Stochastic Processes: Sanitary and Water Resources Engineering (Sanitary & Water Resources Engineering S). New York, NY: McGraw-Hill, 2002. ISBN: 0072817259.
Kohane, I. S., A. T. Kho, and A. J. Butte. Microarrays for an Integrative Genomics. Cambridge, MA: MIT Press, 2002. ISBN: 026211271X.
Links
Hunter, Lawrence. Introduction to Molecular Biology for the Computer Scientist. (PDF)
