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bioRxiv · 10.1101/2022.05.06.487898

NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity

Su, K.·Katebi, A. R.·Kohar, V. R.·Clauss, B.·Gordin, D.·Qin, Z.·Karuturi, R. K. M.·Li, S.·Lu, M.
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Abstract

A major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription-factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in-silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-{beta} induced epithelial-mesenchymal transition and macrophage polarization.

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Su, K., Katebi, A. R., Kohar, V. R., Clauss, B., Gordin, D., Qin, Z., Karuturi, R. K. M., Li, S., Lu, M.. 2022-05-07. NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity. https://doi.org/10.1101/2022.05.06.487898

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