Kai Tan Associate Professor

University of Pennsylvania





研究方向:

Kai Tan lab is interested in gene regulatory networks in normal and disease development. In particular, they focus on understanding how genetic and epigenetic factors interact to control gene expression. Towards this goal, they are conducting interdisciplinary research, combining wet-lab and computation along the following two lines: Model gene regulatory networks in development They are studying gene networks controlling hematopoietic stem cell fate using functional genomic assays
and computational modeling. In this biological context, they are pursuing the following projects: 1) Identify transcriptional enhancers that control developmental- stage-specific gene expression. They are developing computational tools to predict enhancers. They are also developing a high through-put assay to validate their 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. They 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.

近期发表论文:

1. Holmfeldt P, Ganuza M, Marathe H, He B, Hall T, Kang G, Moen J, Parieck J, Saulsberry A, Cico A, Gaut L, McGoldrick D, Finkelstein D, Tan K and McKinney-Freeman S. Functional screen identifies regulators of murine hematopoietic stem cell repopulation. J Exp Med. 2016 Feb 15. pii: jem.20150806. [Epub ahead of print].
2. Huang J, Wang K, Wei P, Liu X, Liu X, Tan K, Boerwinkle E, Potash JB, Han S. FLAGS: A Flexible and Adaptive Association Test for Gene Sets Using Summary Statistics. Genetics 202: 919-29, Mar 2016.
3. He, B and Tan K. Understanding transcriptional regulatory networks using computational models.
Current Opinion in Genes & Development 37: 101-108, Mar 2016.
4. Cao Z, Chen C, He B, Tan K* and Lu C*. : A microfluidic device for profiling genome-wide histone
modifications using 100 cells. Nature Methods 12: 959-962, 2015.
5. Cai Xiongwei, Gao Long, Teng Li, Ge Jingping, Oo Zaw Min, Kumar Ashish R, Gilliland D Gary, Mason
Philip J, Tan Kai, Speck Nancy A: Runx1 Deficiency Decreases Ribosome Biogenesis and Confers Stress Resistance to Hematopoietic Stem and Progenitor Cells. Cell stem cell 17(2): 165-77, Aug 2015.