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NetBID2 (Network-based Bayesian Inference of Drivers, version 2) is a comprehensive algorithm and toolkit developed for hidden driver analysis. Many signaling proteins (e.g., kinases), transcription factors, and other factors that are crucial drivers of phenotypes are not genetically/epigenetically altered or differentially expressed at the mRNA or protein level; hence, the conventional mutation analysis and differential expression analysis may not be able to capture them. Employing the systems biology methods, NetBID2 can reverse-engineer context-specific interactomes and estimate the activities of drivers, including both transcription factors ("TFs") and signaling proteins ("SIGs"), from transcriptomics, proteomics, and phosphoproteomics data. It can provide insights to help understand unclear biological mechanisms and can also identify potential therapeutic targets.
NetBID2 is an upgraded version of NetBID 1.0, which has been published in Nature in 2018. It inherites all of the main functions from NetBID 1.0 and provides many more functions and pipelines with which to perform advanced end-to-end analyses.
More data processing functions:
More visualization functions:
More supporting functions:
NetBID2 is published in Nature Communications! You can find the publication here.
Dong X, Ding L, Thrasher A, Wang X, Liu J, Pan Q, Rash J, Dhungana Y, Yang X, Risch I, Li Y. NetBID2 provides comprehensive hidden driver analysis. Nature Communications. 2023 May 4;14(1):2581.
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