MTFAP: a comprehensive platform for predicting and analyzing master transcription factors.

Area of Science:

• * Molecular Biology
• * Bioinformatics
• * Cancer Research

Background:

• * Master transcription factors (MTFs) regulate gene expression in embryonic stem cells (ESCs), controlling cell fate.
• * MTFs are strongly correlated with cancer initiation and progression.
• * Identifying MTFs presents a significant challenge for researchers.

Purpose of the Study:

• * To develop a user-friendly web resource for predicting and analyzing master transcription factors (MTFs).
• * To provide tools for exploring MTFs across diverse data types and facilitating localized analyses.

Main Methods:

• * Development of a comprehensive web tool, MTFAP, for MTF prediction and analysis.
• * Integration of search and browse functionalities for enhanced user experience.
• * Provision of a Docker file for local analysis capabilities and support for Coltron and CRCmapper identified MTFs.

Main Results:

• * MTFAP offers a centralized platform for MTF identification and characterization.
• * The resource supports various data types and enables both online and local analyses.
• * Enhanced data visualization and further analysis options are available for identified MTFs.

Conclusions:

• * MTFAP addresses the challenge of MTF identification, providing a valuable resource for researchers.
• * The platform facilitates the exploration and analysis of MTFs in ESCs and cancer.
• * MTFAP is freely accessible, promoting broader research in transcription factor roles in development and disease.