Bioinformatics: Motif Finding and Transcription Factor Binding Sites

Understanding gene regulation starts with identifying where transcription factors bind across genomic sequences. This written course provides a clear, step-by-step introduction to computational motif discovery, mathematical representation of sequence patterns, and standard bioinformatic analysis workflows. You will build a solid theoretical foundation and learn how computational tools detect regulatory signals directly from raw sequence data. What you'll learn: - Understand biological mechanisms of transcription factor binding sites and gene expression regulation - Master position weight matrices (PWMs), position frequency matrices, and information content metrics - Explore probabilistic motif search algorithms, including Expectation-Maximization and Gibbs sampling - Apply modern sequence analysis workflows using Python and standard bioinformatics concepts - Evaluate motif significance, statistical enrichment, and false discovery rates The course begins with fundamental terminology and biological context before advancing into quantitative scoring methods and motif-finding algorithms. It is designed for beginners in bioinformatics, computational biology, and data science, requiring no advanced prior knowledge in genomics. Start reading today to master the fundamentals of regulatory sequence analysis.