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2010: Postdoctoral associate, Molecular Biophysics and Biochemistry, Yale University
2009: PhD, Computer Science, Yale University
2003: M.Phil., Computer Science, The University of Hong Kong
1999: B.Eng., Computer Engineering, The University of Hong Kong
Related Disease
Biliary Atresia, Cancer, Diabetes – General, Hirschsprung Disease, Liver Cancer, Nasopharyngeal Carcinoma, Type 2 Diabetes
Phenomena or Processes
Cancer Epigenetics, Gene Regulation, Oncogenes, Posttranslational Modification, Transcriptional Regulation, Tumor Microenvironment
Anatomical Systems and Sites
Endocrine System, General Cell Biology, Immune System and Inflammation, Liver
Research Models
Computational Modeling
Techniques and Technologies
Bioinformatics, Comparative Genomics, Genomics, Machine Learning, Protein-Protein Interactions, Systems Biology
The Yip lab studies gene regulatory mechanisms by means of computational modeling. To facilitate their data-centric approach, they develop novel methods for analyzing large amounts of biological data, including those produced by cutting-edge high-throughput experiments. Their computational models provide a systematic way to investigate the functional effects of different types of perturbations to regulatory mechanisms, which creates testable hypotheses for studying human diseases and facilitates translational research.
Sanford Burnham Prebys scientists say that understanding the potential pitfalls of using artificial intelligence and computational biology techniques in biomedical…
At Sanford Burnham Prebys Graduate School of Biomedical Sciences, students embrace computational methods to enhance their research careers
Researchers from Sanford Burnham Prebys and the Chinese University of Hong Kong have developed a computational approach to predict whether…
ENCODE Project Consortium
Nature 2012 Sep 6 ;489(7414):57-74Gerstein MB, Lu ZJ, Van Nostrand EL, Cheng C, Arshinoff BI, Liu T, Yip KY, Robilotto R, Rechtsteiner A, Ikegami K, Alves P, Chateigner A, Perry M, Morris M, Auerbach RK, Feng X, Leng J, Vielle A, Niu W, Rhrissorrakrai K, Agarwal A, Alexander RP, Barber G, Brdlik CM, Brennan J, Brouillet JJ, Carr A, Cheung MS, Clawson H, Contrino S, Dannenberg LO, Dernburg AF, Desai A, Dick L, Dosé AC, Du J, Egelhofer T, Ercan S, Euskirchen G, Ewing B, Feingold EA, Gassmann R, Good PJ, Green P, Gullier F, Gutwein M, Guyer MS, Habegger L, Han T, Henikoff JG, Henz SR, Hinrichs A, Holster H, Hyman T, Iniguez AL, Janette J, Jensen M, Kato M, Kent WJ, Kephart E, Khivansara V, Khurana E, Kim JK, Kolasinska-Zwierz P, Lai EC, Latorre I, Leahey A, Lewis S, Lloyd P, Lochovsky L, Lowdon RF, Lubling Y, Lyne R, MacCoss M, Mackowiak SD, Mangone M, McKay S, Mecenas D, Merrihew G, Miller DM 3rd, Muroyama A, Murray JI, Ooi SL, Pham H, Phippen T, Preston EA, Rajewsky N, Rätsch G, Rosenbaum H, Rozowsky J, Rutherford K, Ruzanov P, Sarov M, Sasidharan R, Sboner A, Scheid P, Segal E, Shin H, Shou C, Slack FJ, Slightam C, Smith R, Spencer WC, Stinson EO, Taing S, Takasaki T, Vafeados D, Voronina K, Wang G, Washington NL, Whittle CM, Wu B, Yan KK, Zeller G, Zha Z, Zhong M, Zhou X, modENCODE Consortium, Ahringer J, Strome S, Gunsalus KC, Micklem G, Liu XS, Reinke V, Kim SK, Hillier LW, Henikoff S, Piano F, Snyder M, Stein L, Lieb JD, Waterston RH
Science 2010 Dec 24 ;330(6012):1775-87Cao Q, Anyansi C, Hu X, Xu L, Xiong L, Tang W, Mok MTS, Cheng C, Fan X, Gerstein M, Cheng ASL, Yip KY
Nat Genet 2017 Oct ;49(10):1428-1436