Comprehensive analysis of computational approaches in plant transcription factors binding regions discovery

Abstract

Transcription factors (TFs) are regulatory proteins that bind to a specific DNA sequence, known as the transcription factor binding site (TFBS), to regulate the rate of transcription process. For a better understanding of these regulatory proteins, it is crucial to identify these TFBSs across the genomic sequences. The identification of TFBS has been made possible by a number of experimental and computational techniques established during the past few decades. These existing approaches are skewed heavily around human TFBS discovery. The area of TFBS identification in plants is lagging behind due to a lack of experimental data for TFs and very scarce attempts to build plant-specific TFBS identification models. Therefore, to facilitate a better understanding of tools to identify TFBS in plants, here we provide a comprehensive survey of a large number of TFBS identification tools. We have also provided a repository along with corrected scripts, which also has datasets used in the present study. We expect this study to serve as a guide to better the understanding of plant TFBS tools and the care to be taken while applying them, especially during cross-species applications. The corrected scripts of these software are made available athttps://github.com/SCBB-LAB/Comparative-analysis-of-plant-TFBS-software.