Constructing benchmark test sets for biological sequence analysis using independent set algorithms

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

(2021) Alexander Rives et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Improved protein structure prediction using predicted interresidue orientations

(2020) Jianyi Yang et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Remote homology search with hidden Potts models

(2020) Grey W. Wilburn et al.   PLoS Computational Biology

Setting the standards for machine learning in biology

(2019) David T. Jones   NATURE REVIEWS MOLECULAR CELL BIOLOGY

Unified rational protein engineering with sequence-based deep representation learning

(2019) Ethan C. Alley et al.   NATURE METHODS

Correct machine learning on protein sequences: a peer-reviewing perspective

(2015) Ian Walsh et al.   BRIEFINGS IN BIOINFORMATICS

Fast and sensitive protein alignment using DIAMOND

(2014) Benjamin Buchfink et al.   NATURE METHODS

Protein sequence comparison and fold recognition: progress and good-practice benchmarking

(2011) Johannes Söding et al.   CURRENT OPINION IN STRUCTURAL BIOLOGY

Accelerated Profile HMM Searches

(2011) Sean R. Eddy   PLoS Computational Biology

An optimal bit complexity randomized distributed MIS algorithm

(2010) Y. Métivier et al.   DISTRIBUTED COMPUTING

Infernal 1.0: inference of RNA alignments

(2009) E. P. Nawrocki et al.   BIOINFORMATICS