Revision [6213]

This is an old revision of JiguangWang made by JiguangWang on 2013-03-05 23:05:00.

 

Jiguangwang2 ==中文==

Jiguang Wang in Chengdu

Dr. Jiguang Wang

Postdoctoral Research Scientist


Department of Biomedical Informatics
Center for Computational Biology and Bioinformatics
Columbia University College of Physicians and Surgeons


1130 St. Nicholas Ave
ICRC Bldg 8th Floor, Office 804 D
New York, NY 10032

wangjiguang1984-at-gmail.com


Jiguang Wang was born in Cangxian Hebei, China. He got his Ph.D. degree from AMSS of CAS in July 2011, and now is working in Columbia University College of Physicians and Surgeons as a Postdoctoral Research Scientist.



Education and Affiliation


Columbia logo
Postdoctoral Research Scientist (2011.7-now)
Columbia University

MU logo
Visiting Scholar (2011.7-2011.9)
University of Missouri

SIBS logo
Visiting Student (2009.11-2009.12; 2010.3-2010.4; 2010.5-2010.6; 2010.11-2010.12; 2011.5-2011.6)
Shanghai Institutes for Biological Sciences, CAS,

AMSS logo
Ph.D. student in Operations Research and Bioinformatics (2006.9-2011.7)
Academy of Mathematics & Systems Science, CAS

BIT logo
B.S. student in mathematics (2002.9-2006.7)
Beijing Institute of Technology


Exosc3

Research Interests


Research Project





Award and Honors



Selected Publications

  1. APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems.
  1. Whole-exome Sequencing Reveals Recurrent Somatic Mutation Networks in Cancer.
  1. The coding genome of splenic marginal zone lymphoma: activation of NOTCH2 and other pathways regulating marginal zone development.
  1. Rewiring drug-activated p53-regulatory network from suppressing to promoting tumorigenesis.
  1. NOA: a novel Network Ontology Analysis method.
  1. Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.
  1. Modularity optimization in community detection of complex networks.
  1. Remarks on network community properties
  1. Inferring Protein-Protein Interactions Based on Sequences and Interologs in Mycobacterium Tuberculosis.
  1. A unified computational model for revealing and predicting subtle subtypes of cancers.
  1. Network screening of Goto-Kakizaki rat liver microarray data during diabetic progression.


:::All publications:::


Books






Interests






 


Locations of visitors to this page
Valid XHTML :: Valid CSS: :: Powered by WikkaWiki