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Computational biology papers
- G. Gerber, R. Dowell, T. Jaakkola, and D. Gifford.
Automated discovery of functional generality of human gene expression
programs.
PloS Computational biology, 2007.
[link to paper]
- L. Perez-Breva, L. Ortiz, C-H. Yeang, and T. Jaakkola.
Game theoretic algorithms for protein-dna binding.
In Advances in Neural Information Processing Systems 19, 2006.
[pdf]
- Y Qi, A. Rolfe, K. MacIsaac, G. Gerber, D. Pokholok, J. Zeitlinger, T. Danford,
R. Dowell, E. Fraenkel, T. Jaakkola, R. Young, and D. Gifford.
High-resolution computational models of genome binding events.
Nature Biotechnology, 24:963--970, 2006.
[pdf], [pdf]
- Y. Qi, P. Missiuro, A. Kapoor, C. Hunter, T. Jaakkola, D. Gifford, and H. Ge.
Semi-supervised analysis of gene expression profiles for
lineage-specific development in the caenorhabditis elegans embryo.
Bioinformatics, 22(14):417--423, 2006.
[pdf]
- L. Perez-Breva, L. Ortiz, C-H. Yeang, and T. Jaakkola.
Dna binding and games.
MIT CSAIL Technical Report TR-2006-018, 2006.
[pdf]
- C-H. Yeang and T. Jaakkola.
Modeling the combinatorial functions of multiple transcription
factors.
In The Ninth Annual International Conference on Research in
Computational Molecular Biology, 2005.
[pdf]
- C-H. Yeang, H. Mak, S. McCuine, C. Workman, T. Jaakkola, and T. Ideker.
Validation and refinement of gene-regulatory pathways on a network of
physical interactions.
Genome Biology, 6(7):R62, 2005.
[pdf], [link to paper]
- C-H. Yeang, T. Ideker, and T. Jaakkola.
Physical network models.
Journal of Computational Biology, 11(2-3):243--263, 2004.
[pdf]
- Z. Bar-Joseph, G. Gerber, Simon, Gifford I., D., and T. Jaakkola.
Comparing continuous representations of time series expression
profiles to identify differentially expressed genes.
Proceedings of the National Academy of Sciences,
100(18):10146--10151, 2003.
[pdf], [link to paper]
- Z. Bar-Joseph, G. Gerber, T. Lee, N. Rinaldi, J. Yoo, F. Robert, B. Gordon,
E. Fraenkel, T. Jaakkola, R. Young, and D. Gifford.
Computational discovery of gene modules and regulatory networks.
Nature Biotechnology, 21(11):1337--1342, 2003.
[pdf], [link to paper]
- 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):241--256, 2003.
[pdf]
- C-H. Yeang and T. Jaakkola.
Time series analysis of gene expression and location data.
In Proceedings of the Third IEEE Symposium on Bioinformatics and
Bioengineering, pages 305--312, 2003.
[pdf]
- C-H. Yeang and T. Jaakkola.
Physical network models and multi-source data integration.
In The Seventh Annual International Conference on Research in
Computational Molecular Biology, 2003.
[pdf]
- Ziv Bar-Joseph, Erik D. Demaine, David K. Gifford, Angele M. Hamel, Tommi S.
Jaakkola, and Nathan Srebro.
K-ary clustering with optimal leaf ordering for gene expression data.
Bioinformatics (to appear), 2002.
[pdf]
- Z. Bar-Joseph, G. Gerber, D. Gifford, and T. Jaakkola.
A new approach to analyzing gene expression time series data.
In The Sixth Annual International Conference on Research in
Computational Molecular Biology, 2002.
[pdf]
- A. Hartemink, D. Gifford, T. Jaakkola, and R. Young.
Combining location and expression data for principled discovery of
genetic regulatory network models.
In Pacific Symposium on Biocomputing, 2002.
[pdf]
- Z. Bar-Joseph, D. Gifford, and T. Jaakkola.
Fast optimal leaf ordering for hierarchical clustering.
In Proceedings of the Ninth International Conference on
Intelligent Systems for Molecular Biology, 2001.
[pdf]
- A. Hartemink, D. Gifford, T. Jaakkola, and R. Young.
Maximum likelihood estimation of optimal scaling factors for
expression array normalization.
In Microarrays: Optical Technologies and Informatics,
Proceedings of SPIE, volume 4266, 2001.
[postscript], [gzipped postscript]
- A. Hartemink, D. Gifford, T. Jaakkola, and R. Young.
Using graphical models and genomic expression data to statistically
validate models of genetic regulatory networks.
In Pacific Symposium on Biocomputing, volume 6, pages 422--433,
2001.
[pdf]
- T. Jaakkola, M. Diekhans, and D. Haussler.
A discriminative framework for detecting remote protein homologies.
Journal of Computational Biology, 7(1,2):95--114, 2000.
[postscript], [gzipped postscript]
- T. Jaakkola, M. Diekhans, and D. Haussler.
Using the fisher kernel method to detect remote protein homologies.
In Proceedings of the Seventh International Conference on
Intelligent Systems for Molecular Biology, 1999.
[postscript], [gzipped postscript]
- T. Jaakkola and D. Haussler.
Exploiting generative models in discriminative classifiers.
In Advances in Neural Information Processing Systems 11, 1998.
[postscript], [gzipped postscript]
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