Protein sequence design with deep generative models

Generating functional protein variants with variational autoencoders

(2021) Alex Hawkins-Hooker et al.   PLoS Computational Biology

Systematic auditing is essential to debiasing machine learning in biology

(2021) Fatma-Elzahraa Eid et al.   Communications Biology

Deep Dive into Machine Learning Models for Protein Engineering

(2020) Yuting Xu et al.   Journal of Chemical Information and Modeling

The developing toolkit of continuous directed evolution

(2020) Mary S. Morrison et al.   Nature Chemical Biology

Automated Continuous Evolution of Proteins in Vivo

(2020) Ziwei Zhong et al.   ACS Synthetic Biology

Biosystems Design by Machine Learning

(2020) Michael Jeffrey Volk et al.   ACS Synthetic Biology

Signal Peptides Generated by Attention-Based Neural Networks

(2020) Zachary Wu et al.   ACS Synthetic Biology

A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences

(2020) Johannes Linder et al.   Cell Systems

Leveraging Uncertainty in Machine Learning Accelerates Biological Discovery and Design

(2020) Brian Hie et al.   Cell Systems

The Gene Ontology resource: enriching a GOld mine

(2020) et al.   NUCLEIC ACIDS RESEARCH

UniProt: the universal protein knowledgebase in 2021

(2020) et al.   NUCLEIC ACIDS RESEARCH

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

Machine Learning in Enzyme Engineering

(2019) Stanislav Mazurenko et al.   ACS Catalysis

ProtaBank: A repository for protein design and engineering data

(2018) Connie Y. Wang et al.   PROTEIN SCIENCE

Design of metalloproteins and novel protein folds using variational autoencoders

(2018) Joe G. Greener et al.   Scientific Reports

CATH: expanding the horizons of structure-based functional annotations for genome sequences

(2018) Ian Sillitoe et al.   NUCLEIC ACIDS RESEARCH

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

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

The coming of age of de novo protein design

(2016) Po-Ssu Huang et al.   NATURE

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

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

Deep mutational scanning: a new style of protein science

(2014) Douglas M Fowler et al.   NATURE METHODS

MetalPDB: a database of metal sites in biological macromolecular structures

(2012) Claudia Andreini et al.   NUCLEIC ACIDS RESEARCH

A system for the continuous directed evolution of biomolecules

(2011) Kevin M. Esvelt et al.   NATURE

Protein promiscuity and its implications for biotechnology

(2009) Irene Nobeli et al.   NATURE BIOTECHNOLOGY

Exploring protein fitness landscapes by directed evolution

(2009) Philip A. Romero et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY