Edwin Wang Lab

Cancer Systems Biology and Bioinformatics


The largest, manually curated human signaling network

Wang Lab and several other labs together have manually curated human signaling network data from literature since 2005. The data sources include BioCarta, CST Signaling pathways, Pathway Interaction database (PID), iHOP, and many review papers on cell signaling. The signaling network is updated every year. 

 The current network contains more than 6,000 proteins and 63,000 relations. The relations represent activation, inhibition and physical interactions. The physical relations represent complexes that play roles in cell signaling. It has been so far the largest literature-curated human signaling network which can be downloaded here (Version 7).  

An algorithm of cancer biomarker discovery: Multiple Survival Screening (MSS)

This is cancer hallmark-based, two-dimensional (samples and gene sets) re-sampling-based algorithm of identifying cancer biomarkers. MSS-derived gene signatures showed highly robust and more accurate (Nature Communications, 2010).

 The protocol of MSS is in Nature Protocol. The code can be downloaded here (zip file). MSS has been used to generate high quality prognostic markers for breast, prostate and colon cancers, and drug responding markers for ER+ and triple negative breast cancers. Related patents (a, b, c, d and e) have been filed.   

A human cancer signaling map

A cancer signaling map or network (can be downloaded here) has been constructed using cancer mutations and the literature-curated human signaling network. Related work has been published in Molecular Systems Biology, 2007.

Signaling networks of cell proliferation and survival for 16 breast cancer cell lines 

The networks have been constructed by integrating of the human signaling network, genome-wide RNAi knock-down data, exome-sequencing data, gene expression data, and copy number changing data of each breast cancer cell line (luminal and basal lines). Related work has been published in Cell Reports, 2013

The cell line specific networks (zip file), luminal specific network (text file), basalA specific network (text file) and basalB specific network (text file). 

GeneNetMiner, a software for constructing gene regulatory networks by mining literature

The software and user's guide are here.   

eTumorMetastasis, a software for constructing predictive models using genome/whole-exome sequencing data

The software and user's guide are here