Learning protein fitness models from evolutionary and assay-labeled data

Deep diversification of an AAV capsid protein by machine learning

(2021) Drew H. Bryant et al.   NATURE BIOTECHNOLOGY

Low-N protein engineering with data-efficient deep learning

(2021) Surojit Biswas et al.   NATURE METHODS

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

Highly accurate protein structure prediction with AlphaFold

(2021) John Jumper et al.   NATURE

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions

(2021) Amirali Aghazadeh et al.   Nature Communications

Informed training set design enables efficient machine learning-assisted directed protein evolution

(2021) Bruce J. Wittmann et al.   Cell Systems

Neural networks to learn protein sequence–function relationships from deep mutational scanning data

(2021) Sam Gelman et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

TLmutation: Predicting the Effects of Mutations Using Transfer Learning

(2020) Zahra Shamsi et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Machine-learning-guided directed evolution for protein engineering

(2019) Kevin K. Yang et al.   NATURE METHODS

Unified rational protein engineering with sequence-based deep representation learning

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

Quantitative Missense Variant Effect Prediction Using Large-Scale Mutagenesis Data

(2018) Vanessa E. Gray et al.   Cell Systems

Deep generative models of genetic variation capture the effects of mutations

(2018) Adam J. Riesselman et al.   NATURE METHODS

Inferring the shape of global epistasis

(2018) Jakub Otwinowski et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

(2017) Rebecca F. Alford et al.   Journal of Chemical Theory and Computation

Mutation effects predicted from sequence co-variation

(2017) Thomas A Hopf et al.   NATURE BIOTECHNOLOGY

Global analysis of protein folding using massively parallel design, synthesis, and testing

(2017) Gabriel J. Rocklin et al.   SCIENCE

Local fitness landscape of the green fluorescent protein

(2016) Karen S. Sarkisyan et al.   NATURE

Adaptation in protein fitness landscapes is facilitated by indirect paths

(2016) Nicholas C Wu et al.   eLife

Improving landscape inference by integrating heterogeneous data in the inverse Ising problem

(2016) Pierre Barrat-Charlaix et al.   Scientific Reports

Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1

(2015) Matteo Figliuzzi et al.   MOLECULAR BIOLOGY AND EVOLUTION

Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models

(2015) Richard R. Stein et al.   PLoS Computational Biology

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches

(2014) B. E. Suzek et al.   BIOINFORMATICS

Development and Applications of CRISPR-Cas9 for Genome Engineering

(2014) Patrick D. Hsu et al.   CELL

A Comprehensive Biophysical Description of Pairwise Epistasis throughout an Entire Protein Domain

(2014) C. Anders Olson et al.   CURRENT BIOLOGY

Toward rationally redesigning bacterial two-component signaling systems using coevolutionary information

(2014) Ryan R. Cheng et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

The new frontier of genome engineering with CRISPR-Cas9

(2014) J. A. Doudna et al.   SCIENCE

The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

(2014) Jaclyn K. Mann et al.   PLoS Computational Biology

Navigating the protein fitness landscape with Gaussian processes

(2013) P. A. Romero et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Activity-enhancing mutations in an E3 ubiquitin ligase identified by high-throughput mutagenesis

(2013) L. M. Starita et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein

(2013) D. Melamed et al.   RNA

Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models

(2012) Hashem A. Shihab et al.   HUMAN MUTATION

SIFT web server: predicting effects of amino acid substitutions on proteins

(2012) Ngak-Leng Sim et al.   NUCLEIC ACIDS RESEARCH

A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function

(2012) C. L. Araya et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality

(2011) Yves Dehouck et al.   BMC BIOINFORMATICS

Molecular basis of glyphosate resistance - different approaches through protein engineering

(2011) Loredano Pollegioni et al.   FEBS Journal

HMMER web server: interactive sequence similarity searching

(2011) R. D. Finn et al.   NUCLEIC ACIDS RESEARCH

A method and server for predicting damaging missense mutations

(2010) Ivan A Adzhubei et al.   NATURE METHODS

Interpretable Numerical Descriptors of Amino Acid Space

(2009) Alexander G. Georgiev   JOURNAL OF COMPUTATIONAL BIOLOGY

Protein therapeutics: a summary and pharmacological classification

(2007) Benjamin Leader et al.   NATURE REVIEWS DRUG DISCOVERY