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

Autor: Su K; Department of Biomedical Informatics, Emory University, Atlanta, GA, 30322, USA., Katebi A; Department of Bioengineering|, Northeastern University, Boston, MA, 02115, USA.; Center for Theoretical Biological Physics, Northeastern University, Boston, MA, 02115, USA., Kohar V; The Jackson Laboratory, Bar Harbor, ME, 04609, USA., Clauss B; Center for Theoretical Biological Physics, Northeastern University, Boston, MA, 02115, USA.; Genetics Program, Graduate School of Biomedical Sciences, Tufts University, Boston, MA, 02111, USA., Gordin D; Department of Bioengineering|, Northeastern University, Boston, MA, 02115, USA.; Center for Theoretical Biological Physics, Northeastern University, Boston, MA, 02115, USA., Qin ZS; Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, USA., Karuturi RKM; The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA.; Graduate School of Biological Sciences & Eng., University of Maine, Orono, ME, USA., Li S; The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA., Lu M; Department of Bioengineering|, Northeastern University, Boston, MA, 02115, USA. m.lu@northeastern.edu.; Center for Theoretical Biological Physics, Northeastern University, Boston, MA, 02115, USA. m.lu@northeastern.edu.; The Jackson Laboratory, Bar Harbor, ME, 04609, USA. m.lu@northeastern.edu.; Genetics Program, Graduate School of Biomedical Sciences, Tufts University, Boston, MA, 02111, USA. m.lu@northeastern.edu.
Jazyk: angličtina
Zdroj: Genome biology [Genome Biol] 2022 Dec 27; Vol. 23 (1), pp. 270. Date of Electronic Publication: 2022 Dec 27.
DOI: 10.1186/s13059-022-02835-3
Abstrakt: 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-β-induced epithelial-mesenchymal transition and macrophage polarization.
(© 2022. The Author(s).)
Databáze: MEDLINE
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