CCCExplorer is a java-based software that predicts and visualizes the gene signaling network to aid research on crosstalk identification in the tumor microenvironment. CCCExplorer integrates a computational model that we developed to uncover cell-cell communication as a direct and connected network. These cell communications range from ligand-receptor interactions to transcription factors and their target genes.
> Learn more about CCCExplorer software.
- Yeung TL, Sheng J, Leung CS, Li F, Kim J, Ho SY, Matzuk MM, Lu KH, Wong STC*, Mok SC*. Systematic Identification of Druggable Epithelial-Stromal Crosstalk Signaling Networks in Ovarian Cancer. J Natl Cancer Inst. 2018 May 31. PMID: 29860390.
- Choi H, Sheng J, Gao D, Li F, Durrans A, Ryu S, Lee SB, Narula N, Rafii S, Elemento O, Altorki NK, Wong ST*, Mittal V*. Transcriptome analysis of individual stromal cell populations identifies stroma-tumor crosstalk in mouse lung cancer model. Cell Reports. 2015 Feb 24;10(7):1187-201. PMID: 2570482
DrugComboRanker is a computational tool that prioritizes synergistic drug combinations and uncovers their mechanisms of action. It can identify drug combinations by searching for drugs whose targets are enriched in the complementary signaling modules of the disease signaling network to predict top ranked drug combinations and map the drug targets on the disease signaling network to highlight the mechanisms of action of the drug combinations.
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- Huang L, Li F, Sheng J, Xia X, Ma J, Zhan M, Wong ST. DrugComboRanker: drug combination discovery based on target network analysis. Bioinformatics. 2014 Jun 15; 30(12):i228-i236.