Institute of Statistical Science
I am currently an assistant research fellow at the Institute of Statistical Science of Academia Sinica. My research interests focus on three topics in computational biology: 1) Understanding the cross-talks of major signaling and regulatory pathways in cancer, 2) Studying the coupled evolution between components in biomolecular systems, 3) Integrating multiple sources of information to reconstruct the networks of gene regulation and their coupling with other systems, and suggesting new experiments to validate or disambiguate inferred models. Specifically, by examining the data of somatic mutations in cancer, we found that the same set of signaling pathways exhibit qualitatively different couplings in different tumor tissues (FASEB J. 2008). We built a computational model that identifies coevolving nucleic or amino acids from aligned sequences of multiple species. This model can capture different types of interactions (RNA-RNA, amino acid-amino acid, etc.), incorporates phylogenetic information, and requires very few extra free parameters. Using this model, we successfully detected RNA secondary and tertiary interactions (Mol. Biol. Evol. 2007) and established a compendium of coevolving positions among all the known protein domains (PLoS Comp. Biol. 2007). We developed a modeling framework to integrate the data of protein-protein, protein-DNA interactions and knock-out gene expression to identify the “active pathways” that may propagate the knock-out effects to downstream genes (JCB 2004), and validated the pathway models by new knock-out experiments suggested by an information theoretic criterion (Genome Biol. 2005). We further extended this modeling framework to capture the combinatorial regulation of multiple transcription factors (JCB 2006) and the coupling between gene regulation and metabolic reactions (BMC Bioinformatics 2006).
R.A. Beckman, G.S. Schemmann, C.H. Yeang. Impact of genetic dynamics and single-cell heterogeneity on development of nonstandard personalized medicine strategies for cancer. Proceedings, National Academy of Science, U.S.A. 109(36):14586-14591, 2012. [pdf],[pubmed link].
S.D. Li, T. Tagami, Y.F. Ho, and C.H. Yeang. Deciphering causal and statistical relations of molecular aberrations and gene expressions in NCI-60 cell lines. BMC Systems Biology 5:186, 2011. [pdf],[pubmed link].
C.J. Vaske, C. House, T. Luu, B. Frank, C.H. Yeang, N. Lee, and J.M. Stuart. A factor graph nested effects model to identify networks from genetic perturbations. PLoS Computational Biology 9(5):e1000274, 2009. [pdf],[pubmed link].
C.H. Yeang. Identifying coevolving partners from paralogous gene families. Evolutionary Bioinformatics 4:91-107, 2008. [pdf].
C.H. Yeang, J.F.J. Darot, H.F. Noller, D. Haussler. Detecting the coevolution of biosequences – an example of RNA interaction prediction. Molecular Biology and Evolution 24(9):2119-2131, 2007. [pdf], [errata], [pubmed link].
C.H. Yeang, C. Mak, C. Workman, S. McCuine, T. Jaakkola, T. Ideker. Validation and refinement of gene-regulatory pathways on a network of physical interactions. Genome Biology 6:R62.1-R62.10, 2005. [pdf], [pubmed link].
Peer-reviewed Conference Papers
C.H. Yeang, L.C. Huang, W.C.
Liu. Recurrent structural motifs reflect characteristics of distinct
networks. Proceedings, The 2012 IEEE/ACM International Conference on Advances in
Social Networks Analysis and Mining (ASONAM),
C.H. Yeang. A probabilistic graphical
model of quantum systems. Proceedings,
the 9th International Conference on Machine Learning and
C.H. Yeang. Quantifying the strength
of natural selection of a motif sequence. Proceedings, the 10th Workshop on Algorithms in
C.H. Yeang. Exact loopy belief propagation on Euler graphs. Proceedings, the 2010 World Congress in Computer Science, Computer Engineering and Applied Computing (WORLDCOMP), Las Vegas, U.S.A., 2010. [pdf].
C.H. Yeang. Analysis of the bipartite
networks of domain compositions and metabolic reactions. Proceedings, the Second International
Conference on Biomedical Engineering and Informatics (BMEI),
C.H. Yeang, N.A. Baas Evolution of
domain compositions in the metabolic networks of human and Escherichia coli.
Proceedings, the 2009 World Congress in
Computer Science, Computer Engineering and Applied Computing (WORLDCOMP),
P.N. Kanabar, C.J. Vaske, C.H. Yeang, F.H. Yildiz, and J.M. Stuart. Inferring disease-related pathways using a
probabilistic epistasis model. Proceedings,
the 15th Pacific Symposium of Biocomputing (PSB),
L. Perez-Breva, L.E. Ortiz, C.H. Yeang, T. Jaakkola. Game theoretic
algorithms for protein-DNA binding. Proceedings, the 12th
Annual Conference on Neural Information Processing (NIPS),
J. Darot, C.H. Yeang, D. Haussler. Detecting the dependent evolution
of biosequences. Proceedings, the 10th Annual
International Conference of the Research in Computational Molecular Biology
C.H. Yeang and T. Jaakkola. Modeling the combinatorial functions of
multiple transcription factors. Proceedings, the 9th
Annual International Conference of the Research in Computational Molecular
C.H. Yeang and M. Szummer. Continuous Markov random walks. Proceedings,
the 18th conference of uncertainty in artificial intelligence (UAI),
C.H. Yeang and T. Jaakkola. Physical network models and multi-source data
integration. Proceedings, the 7th conference on
research in computational biology (RECOMB),
C.H. Yeang and T. Jaakkola. Time-series analysis of gene expression
and location data. Proceedings, the 3rd IEEE conference
on bioinformatics and bioengineering (BIBE),
C.H. Yeang. An information geometric perspective on active learning.
Proceedings, the 13th European conference on machine learning
C.H. Yeang et al. Molecular classification of multiple tumor types.
Proceedings, the 9th conference on intelligent systems for molecular
C.H. Yeang. Integration of metabolic reactions and gene regulation. In Plants Systems Biology. Series of Methods in Molecular Biology, Vol 553. Belostotsky D.A. (Ed.), 2009.
Inferring regulatory networks from multiple sources of genomic data. Sc. D. Thesis. Supervisor: Tommi Jaakkola. Massachusetts Institute of Technology, 2004. [pdf].
Downloadable Software and Source Codes
Coevolutionary Continuous-Time Markove Process Model (PLoS Comp. Biol. 2007; Mol. Biol. Evol. 2007).
Physical Network Model (JCB 2004; Genome Biol. 2005). The Java plug-in of Cytoscape (written by Craig Mak at Trey Ideker's group) is also available at the supplementary website of the Genome Biology paper.
Past and Current Collaborators
Ker-Chau Li, Institute of Statistical Science, Academia Sinica.
Shyh-Dar Li, Ontario Institute of Cancer Research.
Robert Beckman, Daiichi Sankyo Pharma Development.
Gunter Schemmann, Cancer Institute of
Alex Yu, College of Life Science, National Taiwan University.
Ming Chen, Changhua Christian Hospital, Taiwan.
Na-Sheng Lin, Institute of Plant and Microbial Biology, Academia Sinica.
Center for Molecular Science and Engineering, UC
Josh Stuart, Department of
Biomolecular Engineering, UC
Center for Molecular Biology of RNA, UC
Tommi Jaakkola, Electrical Engineering and Computer Science Department, MIT.
Ideker, Department of Bioengineering, UC
Martin Vingron, Max-Planck Institute for Molecular Genetics.
Nardnisa Sintupisut, Institute of Statistical Science, Academia Sinica.
Andy Chen, Institute of Statistical Science, Academia Sinica.
Summit Suen, Institute of Statistical Science, Academia Sinica.
I-Feng Lan, College of Life Science, National Taiwan University.
Charlie Vaske, Department of Biomolecular Engineering, UC
Pinal Kanabar, Department of Biomolecular Engineering, UC
Jeremy Darot, European Bioinformatics Institute.