Research Abstracts - 2006

Computational Genomics Research Group

David K. Gifford

Computational Genomics

Our laboratory develops new machine learning techniques and algorithms to model the transcriptional regulatory networks that control gene expression programs in living cells. We have a very productive interdisciplinary collaboration with leading biologists that has allowed us to tackle extraordinarily difficult and interesting problems that underlie cellular function and development. For example, we have developed probabilistic models of cellular function (PSB), built a comprehensive model of the yeast cell cycle (Science 2002), participated in the discovery of the draft transcriptional regulatory code of yeast (Nature 2004), and helped uncover how key diabetes related transcription factors regulate cellular function in the human pancreas and liver (Science 2004). Current work in our laboratory is examining how we can computationally model chromatin modifying complexes that are associated with the genome of living yeast cells. New kinds of mechanistic computational models are necessary to capture how chromatin structure encodes cellular memory, and how the state of this memory is used to control gene expression. In particular, we are investigating new modular graphical models that use mechanistic constraints to describe biological mechanism.

A new focus is an interdisciplinary project that seeks to build computational models of the transcriptional regulatory networks that control the differentiation of specific cell types. Elucidating these regulatory networks will enable us to define the regulatory processes that determine a cell's progress to its terminally differentiated state, and position us to differentiate embryonic stem (ES) cells for the treatment of debilitating human diseases. New computational techniques for elucidating transcriptional regulatory networks based on the integration of diverse high-throughput experimental data (genome sequence, chromatin structure, transcription factor-DNA binding, gene expression) provide a powerful foundation for discovering the detailed mechanisms of regulatory network control of cell differentiation during development. .

References:

C. Harbison, D. B. Gordon, T. I Lee, N. J. Rinaldi, K. D. MacIsaac, T. W. Danford, N. M. Hannett, J.B. Tagne, D. B. Reynolds, J. Yoo, E. G. Jennings, J. Zeitlinger, D. K. Pokholok, M. Kellis, P. A. Rolfe, K. T. Takusagawa, E. S. Lander, D. K. Gifford, E. Fraenkel, and R. A. Young. "Transcriptional regulatory code of a eukaryotic genome." Nature, 431:99-104, September, 2004.

D. T. Odom, N. Zizlsperger, D. B. Gordon, G. W. Bell, N. J. Rinaldi, H. L. Murray, T. L. Volkert, J. Schreiber, P. A. Rolfe, D. K. Gifford, E. Fraenkel, G. I. Bell, R. A. Young. "Control of Pancreas and Liver Gene Expression by HNF Transcription Factors." Science, 303:1378-1381, February, 2004.

K. T. Takusagawa, D. K. Gifford. "Negative Information for Motif Discovery." Pacific Symposium on Biocomputing, 9:360-371, 2004.

Z. Bar-Joseph, G. Gerber, T. I. Lee, N. J. Rinaldi, J. Y. Yoo, F. Robert, D. B. Gordon, E. Fraenkel, T. S. Jaakkola, R. A. Young, D. K. Gfford. "Computational discovery of gene modules and regulatory networks." Nature Biotechnology, 21, pp. 1337-1342 November, 2003.

Z. Bar-Joseph, G. Gerber, D. Gifford, T. Jaakkola and I. Simon. "Continuous Representations of Time Series Gene Expression Data." Journal of Computational Biology, 10(3-4) pp. 241-256.

Ziv Bar-Joseph, Erik D. Demaine, David K. Gifford, Ang M. Hamel, Tommy S. Jaakkola and Nathan Srebro. "K-ary Clustering with Optimal Leaf Ordering for Gene Expression Data." Bioinformatics, Vol. 19, No. 9, 2003.T.I. Lee, N. J. Rinaldi, F. Robert, D. T. Odom, Z. Bar-Joseph, G. K. Gerber, ... D. K Gifford and R. A. Young. "Transcriptional Regulatory Networks In Saccharomyces cerevisiae." Science, 298:799-804 (2002)

Alexander J. Hartemink, David K. Gifford, Tommi S. Jaakkola, and Richard A. Young. "Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Network Models." Pacific Symposium on Biocomputing 2002, Kauai, January 2002.

Alexander J. Hartemink, David K. Gifford, Tommi S. Jaakkola, and Richard A. Young. "Bayesian Methods for Elucidating Genetic Regulatory Networks." IEEE Intelligent Systems in Biology, Vol. 17, No. 2, pp. 37-43.

I. Simon, J. Barnett, N. Hannett, C. T. Harbison, R. J. Rinaldi, T. L. Volkert, J. J. Wyrick, J.Zeitlinger, D. K. Gifford, T. S. Jaakkola, R. A. Young. "Serial Regulation of Transcriptional Regulators in the Yeast Cell Cycle." Cell, 106, Sept., 2001, p. 667-708.

Z. Bar-Joseph, G. Gerber, D. Gifford, T. Jaakkola and I. Simon. "A new approach to analyzing gene expression time series data." In Proceedings of The Sixth Annual International Conference on Research in Computational Molecular Biology (RECOMB), 2002, pp 39-48.

David K. Gifford. "Blazing pathways through genetic mountains." Science 2001 Sep 14;293(5537):2049-51.

Z. Bar-Joseph, D. Gifford, and T. Jaakkola. "Fast optimal leaf ordering for hierarchical clustering." Bioinformatics(Proceedings of ISMB 2001), 17(S1), 2001, pp 22-29 .

Alexander J. Hartemink, David K. Gifford, Tommi S. Jaakkola, and Richard A. Young. "Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks." Pacific Symposium on Biocomputing 2001, Hawaii, January 2001.

Alexander J. Hartemink, David K. Gifford, Tommi S. Jaakkola, and Richard A. Young. "Maximum Likelihood Estimation of Optimal Scaling Factors for Expression Array Normalization." SPIE BiOS 2001, San Jose, California, January 2001.