Transcription factors (TFs) are pivotal regulatory proteins thatbind to DNA sequences called transcription factor binding sites (TFBSs) to regulate the expression of genes. When, where, and how genes are active or repressed are all fundamentally determined by these binding sites. An overview of the biological significance of TFBSs, their role in gene regulation, and the consequences of their failure in disease are given in this article. The study also examines important uses of TFBS prediction in plant and animal biology, such as evolutionary analysis, illness research in animals, and crop stress tolerance. Different methodologies including bioinformatics tools for TFBS identification have been discussed in this article. Then using the JASPAR database and the BertSNR deep learning model, a case study involving the transcription factor ZNF594 is provided, showcasing contemporary computational methods in TFBS prediction.
