Institute of Statistical Science
I am currently an associate research fellow at the Institute of Statistical Science of Academia Sinica. My research interests focus on two areas in computational biology: 1)cancer genomics, 2)molecular evolution. In cancer genomics, we examined the combinatorial patterns of somatic mutations in cancer and related them to pathway and functional implications (FASEB J. 2008). We also developed a statistical model and inference algorithms to integrate multiple types of molecular aberration data (BMC Bioinformatics 2010) and applied them to large-scale cancer genomic data analysis (BMC Systems Biology 2011, Nucleic Acids Res. 2013). In addition to data analysis, we also proposed optimization algorithms for combinatorial treatments for a heterogeneous tumor population (PNAS 2012). In molecular evolution, we built a computational model that identifies coevolving nucleic or amino acids from aligned sequences of multiple species (Mol. Biol. Evol. 2007; PLoS Comp. Biol. 2007). We also proposed an algorithm that reconstructs the evolutionary history of biomolecular networks according to parsimony (Genome. Biol. & Evol. 2012). Furthermore, we developed a model to quantify the strength of purifying selection of sequence motifs and applied this method to exhaustively identify functional 10-mers from mammalian promoters (Nucleic Acids Res. 2013).
I.Y. Lin, F.L. Chiu, C.H. Yeang. H.F. Chen, C.Y. Chuang, S.Y. Yang, P.S. Hou, N. Sintupisut, H.N. Ho, H.C. Kuo, K.I. Lin. Suppression of the SOX2 neural rffector gene by PRDM1 promotes human germ cell fate in embryonic stem cells. Stem Cell Reports 2(2):189-204, 2014. [pdf],[pubmed link].
N. Sintupisut, C.H. Yeang. Sequence mutations of genes pertaining to malignancy in cancer. Journal of Data Science 11:673-714, 2013. [pdf].
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
Inferring Association Modules from Integrated Cancer Genomic Data (Nucleic Acids Res. 2013; BMC Systems Biology. 2011).
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, Academia Sinica.
Ben-Yang Liao, National Health Research Institute.
Henry Horng-Shing Lu, National Chiao-Tung University.
Shyh-Dar Li, Ontario Institute of Cancer Research.
Kuo-I Lin, Academia Sinica.
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, 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.
Current and Past Student/Postdoc Collaborators
Andrew Woolston, Institute of Statistical Science, Academia Sinica.
Mirrian Ho, Genome Research Center, Academia Sinica.
Chih-Hsu Lin, Institute of Statistical Science, Academia Sinica.
Mariya Simak, The International Graduate Program, Academia Sinica.
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.