Kai Tan, PhD

Associate Professor of Internal Medicine - Bioinformatics and Computational Biology

Contact Information


BS, Beloit College
PhD, Washington University in Saint Louis

Post Doctoral Fellow, University of California San Diego

Education/Training Program Affiliations

Interdisciplinary Graduate Program in Genetics, Interdisciplinary Graduate Program in Informatics, Interdisciplinary Graduate Program in Neuroscience, Medical Scientist Training Program

Center, Program and Institute Affiliations

Center for Bioinformatics and Computational Biology, Center for Gene Therapy of Cystic Fibrosis and other Genetic Diseases, Environmental Health Sciences Research Center, Holden Comprehensive Cancer Center, Institute for Clinical and Translational Science, Iowa Institute of Human Genetics.

Research Summary

Our lab is interested in gene regulatory networks in normal and disease development. In particular, we focus on understanding how genetic and epigenetic factors interact to control gene expression. Towards this goal, we are conducting interdisciplinary research, combining wet-lab and computation along the following two lines: Model gene regulatory networks in development We are studying gene networks controlling hematopoietic stem cell fate using functional genomic assays and computational modeling. In this biological context, we are pursuing the following projects: 1) Identify transcriptional enhancers that control developmental-stage-specific gene expression. We are developing computational tools to predict enhancers. We are also developing a high through-put assay to validate our computational predictions. 2) Understand the interaction between transcription factor binding and chromatin modifications and its effect on gene expression during hematopoietic stem cell fate specification. 3) Integrate genomic and interactome data to discover gene regulatory pathways during hematopoietic stem cell fate specification. Discover molecular networks as biomarkers for human diseases Molecular interaction networks are increasingly serving as tools to unravel the basis of human diseases. We are developing network-based approaches to identifying disease-related sub-networks that can serve as biomarkers for the diagnosis and prognosis of diseases and as candidates for novel therapeutics.


Fan, R., Bonde, S., Gao, P., Sotomayor, B., Chen, C., Mouw, T., Zavazava, N. & Tan, K. (2012). Dynamic HoxB4 Regulatory Network During Hematopoietic Stem Cell Development. Blood, 119, e139-147.

Tan, K., Soshnev, A. A., He, B., Baxley, R. M., Jiang, N., Hart, C. M. & Geyer, P. K. (2012). Genome-wide studies of the multi-zinc finger Drosophila Suppressor of Hairy-wing protein in the ovary. Nucleic Acids Res., 40(12), 5415-31.

Tan, K. (2012). Chromatin Analysis Technical Guide. Genome Technology.

Tan, K., Zavazava, N., Fan, R., Bonde, S., Gao, P., Sotomayor, B., Chen, C. & Mouw, T. (2012). Regulatory Network During Hematopoietic Stem Cell Development. Blood, 119(19), 139-47.

Tan, K., Ma, X. & Gao, L. (2012). N-module: An information theoretic framework for discovering conserved modules in multiple cancer gene co-expression networks. The Cancer Genome Atlas' 2nd Annual Scientific Symposium: Enabling Cancer Research Through TCGA.

Teng, L., Tan, K. (2012). Finding combinatorial histone code by semi-supervised biclustering. BMC Genomics, 13, 301.

Kim, J., Gao, L. & Tan, K. (2012). Multi-analyte Network Markers for Tumor Prognosis. Plos One, 7(12), e52973.

Tan, K., Teng, L. (2012). Discovering distal regulatory elements by integrating multiple types of chromatin state maps. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine.

Teng, L., Firpi, H. & Tan, K. (2011). Enhancers in embryonic stem cells are enriched for transposable elements and genetic variations associated with cancers. Nucleic Acids Res, 39, 7371-1.

Ucar, D., Hu, Q. & Tan, K. (2011). Combinatorial chromatin modification patterns in the human genome revealed by subspace clustering. Nucleic Acids Res, 39, 4063-75.

Tan, K., Teng, L. & Firpi, H. (2011). Global Perspectives on Transcriptional Enhancer Evolution and Disease Link. Gordon Conference on Epigenetics: Mechanisms, Development and Disease.

Tan, K., Ravasi, T., Cannistraci, C. V., Katayama, S. & Bajic, V. B. (2010). FANTOM consortium & Riken Omics Science Center. An atlas of combinatorial transcriptional regulation in mouse and man. Cell, 140, 744-752.

Firpi, H. A., Ucar, D. & Tan, K. (2010). Discover regulatory DNA elements using chromatin signatures and artificial neural network. Bioinformatics, 26, 1579-86.

Kim, J., Tan, K. (2010). Discover protein complexes in protein-protein interaction networks using parametric local modularity. BMC Bioinformatics, 11(1), 521.

Tan, K., Kuo, D., Licon, K., Bandyopadhyay, S., Chuang, R., Luo, C., Catalana, J., Ravasi, J. & Ideker, T. (2010). Co-evolution within a transcriptional network by compensatory trans and cis mutations. Genome Research, 20(12), 1672-8.

Tan, K., Kuo, D., Zinman, G., Ravasi, T., Bar-Joseph, Z. & Ideker, T. (2010). Evolutionary divergence in the fungal response to fluconazole revealed by soft clustering. Genome Biology.

Tan, K., Ucar, D., Hu, Q. & Firpi, H. (2010). Combinatorial chromatin modification patterns in the human genome revealed by subspace clustering. International Conference on Intelligent Systems for Molecular Biology.

Tan, K. (2009). 13. The FANTOM consortium & Riken Omics Science Center. 2009. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nature Genetics, 41, 553-562.

Tan, K., Tegner, J. & Ravasi, T. (2008). Integrated approaches to uncover transcriptional regulatory networks in mammalian cells. Genomics, 91(3), 219-231.

Tan, K., Feizi, H., Luo, C., Fan, S., Ravasi, T. & Ideker, T. (2008). A systems approach to delineate functions of paralogous transcription factors: Role of the Yap family in the DNA damage response. Proc. Natl. Acad., 105(8), 2934-2939.

Tan, K., Shlomi, T., Feizi, H., Ideker, T. & Sharan, R. (2007). Transcriptional regulation of protein complexes within and across species. Proc. Natl. Acad. Sci, 104(4), 1283-1288.

Tan, K., Ideker, T. (2007). Protein interaction networks. In Biological networks. World Scientific, New Jersey.

Tan, K., McCue, L. A. & Stormo, G. D. (2005). Making connections between novel transcription factors and their DNA motifs. Genome Res, 15, 312-320.

Ideker, T., Tan, K. & Uetz, P. (2005). Visualization and integration of protein interaction networks. In Protein-Protein Interactions: A molecular cloning manual. Cold Spring Harbor Laboratory Press.

Tan, K., Liu, J. J. & Stormo, G. D. (2003). Computational identification of the Spo0A-phosphate regulon that is essential for the cellular differentiation and development in Gram-positive spore forming bacteria. Nucleic Acids Res, 31, 6891-6903.

Tan, K., Stormo, G. D. (2002). Mining Genome databases to identify and understand new gene regulatory systems. Curr Opin Microbiol, 5, 149-153.

Tan, K., Moreno-Hagelsieb, G., Collado-Vides, J. & Stormo, G. D. (2001). A comparative genomics approach to prediction of new members of regulons. Genome Res, 11, 566-584.

Tan, K., Lu, D., Futterer, K., Korolev, S., Zheng, X., Waksman, G. & Sadler, J. E. (1999). Crystal structure of enteropeptidase light chain complexed with an analog of the trypsinogen activation peptide. Journal of Molecular Biology, 292, 361-373.