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Revealing evolutionary constraints on proteins through sequence analysis

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Exploring protein sequence–function landscapes

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From discovery to application: Enabling technology-based optimizing carbonyl reductases biocatalysis for active pharmaceutical ingredient synthesis

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Natural Evolution Provides Strong Hints about Laboratory Evolution of Designer Enzymes

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CLADE 2.0: Evolution-Driven Cluster Learning-Assisted Directed Evolution

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Combining evolutionary and assay-labelled data for protein fitness predictionPreprint

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Genome-wide prediction of disease variants with a deep protein language model

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Deep generative models of genetic variation capture mutation effectsPreprint

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In vivo functional phenotypes from a computational epistatic model of evolution

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A Comparison of the Maximum Entropy Principle Across Biological Spatial Scales

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Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data

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AMELIE accelerates Mendelian patient diagnosis directly from the primary literaturePreprint

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Efficient generative modeling of protein sequences using simple autoregressive modelsPreprint

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Generalizable and scalable protein stability prediction with rewired protein generative models

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Ancestral sequence reconstruction - An underused approach to understand the evolution of gene function in plants?

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Machine Learning for Protein Engineering

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Non-Identifiability and the Blessings of Misspecification in Models of Molecular Fitness

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Proximal Exploration for Model-guided Protein Sequence DesignPreprint

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Is Novelty Predictable?Preprint

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Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery

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ESM ‐scan—A tool to guide amino acid substitutions

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LYRUS: a machine learning model for predicting the pathogenicity of missense variants

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Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

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Deciphering polymorphism in 61,157 Escherichia coli genomes via epistatic sequence landscapes

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Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods

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Inferring protein fitness landscapes from laboratory evolution experiments

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Plug & play directed evolution of proteins with gradient-based discrete MCMC

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Zero-shot transfer of protein sequence likelihood models to thermostability prediction

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Structure and energy based quantitative missense variant effect analysis provides insights into drug resistance mechanisms of anaplastic lymphoma kinase mutations

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DCA for genome-wide epistasis analysis: the statistical genetics perspective

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3D spatial organization and network-guided comparison of mutation profiles in Glioblastoma reveals similarities across patients

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A large‐scale survey of pairwise epistasis reveals a mechanism for evolutionary expansion and specialization of PDZ domains

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Deep Mutational Scanning of Viral Glycoproteins and Their Host Receptors

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Understanding epistatic networks in the B1 β-lactamases through coevolutionary statistical modeling and deep mutational scanning

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Structural and computational design of a SARS-CoV-2 spike antigen with improved expression and immunogenicity

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DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

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MARS and RNAcmap3: The Master Database of All Possible RNA Sequences Integrated with RNAcmap for RNA Homology Search

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EvoAI enables extreme compression and reconstruction of the protein sequence space

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Evolutionary couplings detect side-chain interactions

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Prediction of mutation effects using a deep temporal convolutional network

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Dissection of pleiotropic effects of variants in and adjacent to F8 exon 19 and rescue of mRNA splicing and protein function

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Direct coupling analysis of epistasis in allosteric materials

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Optimal Design of Stochastic DNA Synthesis Protocols based on Generative Sequence ModelsPreprint

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Evaluation of Machine Learning-Assisted Directed Evolution Across Diverse Combinatorial Landscapes

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Accurate prediction of functional effect of single amino acid variants with deep learning

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Learning the shape of protein microenvironments with a holographic convolutional neural network

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Phylogenetic Weighting Does Little to Improve the Accuracy of Evolutionary Coupling Analyses

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Aligning biological sequences by exploiting residue conservation and coevolution

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Evolution-aided engineering of plant specialized metabolism

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A Deep SE(3)-Equivariant Model for Learning Inverse Protein FoldingPreprint

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TM-Vec: template modeling vectors for fast homology detection and alignmentPreprint

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Alignment-based Protein Mutational Landscape Prediction: Doing More with Less

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ProtMamba: a homology-aware but alignment-free protein state space model

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Genome wide analyses reveal the role of mutator phenotypes in Mycobacterium tuberculosis drug resistance emergence

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How artificial intelligence is reengineering protein engineering

Listgarten, J., & Jiang, H. (2026) · Science · doi:10.1126/science.aec8444 · Cited by 20

Delineation of functionally essential protein regions for 242 neurodevelopmental genes

Iqbal, S., Brünger, T., Pérez‐Palma, E., Macnee, M., Brunklaus, A., Daly, M. J., Campbell, A. J., Hoksza, D., May, P., & Lal, D. (2022) · Brain · doi:10.1093/brain/awac381 · Cited by 17

Deep mutational scanning of hepatitis B virus reveals a mechanism for cis-preferential reverse transcription

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Accelerating protein engineering with fitness landscape modelling and reinforcement learning

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Evolutionary coupling analysis identifies the impact of disease-associated variants at less-conserved sites

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Leri: A web-server for identifying protein functional networks from evolutionary couplings

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The Cancermuts software package for the prioritization of missense cancer variants: a case study of AMBRA1 in melanoma

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Selection originating from protein stability/foldability: Relationships between protein folding free energy, sequence ensemble, and fitness

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Probabilistic genotype-phenotype maps reveal mutational robustness of RNA folding, spin glasses, and quantum circuits

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Gene regulatory networks: from correlative models to causal explanations

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Systematic enhancement of protein crystallization efficiency by bulk lysine‐to‐arginine ( KR ) substitution

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Novel therapies for diabetes mellitus in pregnancy

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Multiplexed assays reveal effects of missense variants in MSH2 and cancer predisposition

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