학술논문

TRANSPARENT: a Python tool for designing transcription factor regulatory networks.
Document Type
Article
Source
Soft Computing - A Fusion of Foundations, Methodologies & Applications. May2023, Vol. 27 Issue 10, p6261-6266. 6p.
Subject
*TRANSCRIPTION factors
*BINDING sites
*GENE expression
*DATABASES
Language
ISSN
1432-7643
Abstract
Transcription factors are proteins able to selectively bind DNA short traits, namely transcription factors binding sites, in order to regulate gene expression in terms of both repression and activation. Despite plenty of studies focusing on transcription factors and on the role they play in specific biological tasks or diseases, is available in the literature, to our knowledge there is no tool able to automatically provide a list of transcription factors involved in this task and the associated interaction network through a solid computational analysis. TRANScriPtion fActor REgulatory NeTwork (TRANSPARENT) is a user-friendly Python tool designed to help researchers in studying given biological tasks or given diseases in human, by identifying transcription factors controlling and regulating the expression of genes associated with that task or disease. The tool takes in input a list of gene IDs and provides (1) a set of transcription factors that are significantly associated with the input genes, (2) the correspondent P values (i.e., the probability that this observed association was driven by chance) and (3) a transcription factor network that can be directly visualized through STRING database. The effectiveness and reliability of the tool were assessed by applying it to two different test cases: schizophrenia and autism disorders. The obtained results clearly show that identified TFs, for both datasets, are significantly associated with those disorders, in terms of both gene enrichment and coherence with the literature. The proposed tool TRANSPARENT can be a useful instrument to investigate transcription factor networks and unveil the role that TFs play in given biological tasks and diseases. [ABSTRACT FROM AUTHOR]