Learning generative models for protein fold families

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Machine learning‐based prediction of enzyme substrate scope: Application to bacterial nitrilases

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Modeling Sequence-Space Exploration and Emergence of Epistatic Signals in Protein Evolution.

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Evolution of protein interactions: From interactomes to interfaces

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Direct Coupling Analysis for Protein Contact Prediction

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Large-Scale Conformational Transitions and Dimerization Are Encoded in the Amino-Acid Sequences of Hsp70 Chaperones

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Dynamic Profiling of β-Coronavirus 3CL Mpro Protease Ligand-Binding Sites

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Computational and cellular studies reveal structural destabilization and degradation of MLH1 variants in Lynch syndrome

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Structure and Sequence Analyses of Clustered Protocadherins Reveal Antiparallel Interactions that Mediate Homophilic Specificity

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Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp Operon

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Co-evolution-based prediction of metal-binding sites in proteomes by machine learning

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Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease

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End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

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Structure determination of the HgcAB complex using metagenome sequence data: insights into microbial mercury methylation

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Enhanced unbiased sampling of protein dynamics using evolutionary coupling information

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Structure-based enzyme engineering improves donor-substrate recognition of Arabidopsis thaliana glycosyltransferases

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Antiparallel protocadherin homodimers use distinct affinity- and specificity-mediating regions in cadherin repeats 1-4

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Applications of contact predictions to structural biology

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Single Molecule Data Analysis: An Introduction

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Improved structure-related prediction for insufficient homologous proteins using MSA enhancement and pre-trained language model

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Conservation of coevolving protein interfaces bridges prokaryote–eukaryote homologies in the twilight zone

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Structure Learning for Generative Models of Protein Fold Families

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GENERALIST: An efficient generative model for protein sequence familiesPreprint

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GENERALIST: A latent space based generative model for protein sequence families

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Profile Conditional Random Fields for Modeling Protein Families with Structural InformationPreprint

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