Accurate Protein Sequence Alignment Methods and Challenges
Explore the current state-of-the-art methods and challenges in aligning over a million protein sequences. Discover progressive, seed-based, and one-to-all methods, along with benchmarks and experimental studies highlighting the accuracy and scale challenges faced in bioinformatics.
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Presentation Transcript
Towards the accurate alignment of over a million protein sequences: Current state of the art Santus, Garriga, Deorowicz, Gudy , Notredame 2023 Presented by: Ian Chen
Outline - - - - - Challenges in MSA Current methods Benchmarks Experimental study Future directions
Challenge: Scale - Earth BioGenome project - 1.5 million genomes, 1 billion homologous sequences Excessive memory requirements Accuracy decreases with scale - Not only a computational challenge - -
Progressive Methods - - - MAFFT DPPartTree, ClustalOmega, FAMSA, KAlign 3 Estimate guide tree pairwise align leaf to root Computing guide tree - Distance based methods - NJ, UPGMA, - Pairwise distance calculation - Subquadratic runtime? - Subquadratic memory? - ML methods - FastTree
Seed-based Methods - - - - PASTA, MAGUS, UPP, Regressive, MUSCLE Small seed MSA merge sequences Consistency Divide and Conquer - Accuracy: Small scale accurate methods - Scale: Partial guide trees
One-to-all Methods - - learnMSA, MMseqs2 Build representative model of family stack sequences - Database - Hidden Markov Model
Benchmarks - Structure based validations - HomFam, extHomFam, - Pfam + HOMSTRAD Bootstrap Support - GUIDANCE - Transitive Consistency Score Predictive Structure - QuanTest - -
Experimental Study - - - Dataset: extHomFam Criterion: SP (recall), TC (precision) Methods: Kalign, ClustalOmega, PartTree, UPP, learnMSA, FAMSA, Regressive
Future Directions - - - - Efficient Hardware: GPU, Multicore Machine learning Sequence vs Structure MSA Alignment Free methods
Bibliography - Santus, L., Garriga, E., Deorowicz, S., Gudy , A., & Notredame, C. (2023). Towards the accurate alignment of over a million protein sequences: Current state of the art. Current Opinion in Structural Biology, 80, 102577. doi:10.1016/j.sbi.2023.102577
