End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman
Samantha Petti, Nicholas Bhattacharya, Roshan Rao, Justas Dauparas, Neil Thomas, Juannan Zhou, Alexander M. Rush, Peter K. Koo, Sergey Ovchinnikov
This paper introduces a differentiable Smith-Waterman algorithm to jointly learn multiple sequence alignments and downstream tasks, showing improvements in contact prediction and structure prediction.
Bioinformatics · Nov 8, 2022Peer-reviewedBioinformatics