L31: Pattern matching algorithm again | using burrows wheeler transform(bwt) & suffix array

Welcome to Lecture 31 of the course "Algorithmic Thinking in Bioinformatics" Associate Prof. Manikandan Narayanan. Full Course: https://study.iitm.ac.in/ds/course_pages/BSBT4001.html Video Overview Explore efficient pattern matching techniques using the Burrows Wheeler Transform and suffix arrays in this engaging lecture. Learn how these powerful data structures enable fast and scalable searching within large genomic sequences while maintaining linear time complexity. We will compare their performance and memory efficiency to traditional suffix trees, highlighting why BWT and suffix arrays are widely used in modern bioinformatics. The lecture also introduces strategies for extending pattern matching to handle inexact matches, an essential feature for detecting mutations and variations in personalized genomes. In addition, we will touch on methods for addressing more complex genome rearrangements such as inversions and translocations. Whether you are working with genomic data or studying algorithm design, this session offers a clear and practical guide to advanced pattern matching in the context of genome analysis. About IIT Madras' online Bachelor of Science programme IIT Madras offers four-year BS programmes that aim to provide quality education to all, irrespective of age, educational background, or location. The BS programme has multiple levels, which provide flexibility to students to exit at any of these levels. Depending on the courses completed and credits earned, the learner can receive a Foundation Certificate from IITM CODE (Centre for Outreach and Digital Education), Diploma(s) from IIT Madras, or BSc/BS Degrees from IIT Madras. For more details, Visit: https://www.iitm.ac.in/academics/study-at-iitm/non-campus-bs-programmes #BurrowsWheelerTransform #BWT #SuffixArray #SuffixTree #PatternMatching #Genome #Genomics #Bioinformatics #Algorithms #DataStructures #SequenceAlignment #InexactMatching #Mutations #ReadMapping #LinearTime #ComputationalBiology #GenomeAnalysis #PrecisionMedicine #GenomicData #VariantDetection #SequenceSearch #BioinformaticsAlgorithms #NextGenerationSequencing #GenomicRearrangements #InversionDetection #TranslocationAnalysis #BiomedicalInformatics #GeneticVariation