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Review
. 2023 Dec;23(23-24):e2200462.
doi: 10.1002/pmic.202200462. Epub 2023 Sep 14.

Computational tools for inferring transcription factor activity

Dennis Hecker  1   2   3 , Michael Lauber  4 , Fatemeh Behjati Ardakani  1   2   3 , Shamim Ashrafiyan  1   2   3 , Quirin Manz  4 , Johannes Kersting  4   5 , Markus Hoffmann  4   6   7 , Marcel H Schulz  1   2   3 , Markus List  4
Affiliations
Review

Computational tools for inferring transcription factor activity

Dennis Hecker et al. Proteomics. 2023 Dec.

Abstract

Transcription factors (TFs) are essential players in orchestrating the regulatory landscape in cells. Still, their exact modes of action and dependencies on other regulatory aspects remain elusive. Since TFs act cell type-specific and each TF has its own characteristics, untangling their regulatory interactions from an experimental point of view is laborious and convoluted. Thus, there is an ongoing development of computational tools that estimate transcription factor activity (TFA) from a variety of data modalities, either based on a mapping of TFs to their putative target genes or in a genome-wide, gene-unspecific fashion. These tools can help to gain insights into TF regulation and to prioritize candidates for experimental validation. We want to give an overview of available computational tools that estimate TFA, illustrate examples of their application, debate common result validation strategies, and discuss assumptions and concomitant limitations.

Keywords: bioinformatic tools; gene regulation; gene regulatory networks; transcription factor activity.

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References

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