arXiv:2312.02994
High Performance Multiple Sequence Alignment Algorithms for Comparison of Microbial Genomes
원문 초록
Advances in gene sequencing have enabled in silico analyses of microbial genomes and have led to the revision of concepts of microbial taxonomy and evolution. We explore deficiencies in existing multiple sequence global alignment algorithms and introduce a new indexing scheme to partition the dynamic programming algorithm hypercube scoring tensor over processors based on the dependency between partitions to be scored in parallel. The performance of algorithms is compared in the study of rpoB gene sequences of Mycoplasma species.
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MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
PEvoLM: Protein Sequence Evolutionary Information Language Model
PoET: A generative model of protein families as sequences-of-sequences
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation
ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis
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