A Comparative Analysis of Computational Methods for Motif Refinement

Abstract

Finding patterns in DNA sequences, a challenging task in molecular biology and computer science, plays a crucial role in understanding gene expression and transcription regulation. This article explores various computational methods for identifying transcription factor binding sites TFBS and regulatory motifs in DNA sequences. We discuss the significance of these motifs in gene expression and disease susceptibility research. The article categorizes motif discovery algorithms into enumerative, probabilistic, combinatorial, and nature - inspired approaches, highlighting their strengths and limitations. It emphasizes the need for a comprehensive motif discovery tool that can handle diverse motif types, perform global searches efficiently, and reduce user - defined parameters.