Machine-learning-guided directed evolution for protein engineering

Machine learning-assisted directed protein evolution with combinatorial libraries

(2019) Zachary Wu et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

DeepSol: a deep learning framework for sequence-based protein solubility prediction

(2018) Sameer Khurana et al.   BIOINFORMATICS

mGPfusion: predicting protein stability changes with Gaussian process kernel learning and data fusion

(2018) Emmi Jokinen et al.   BIOINFORMATICS

Learned protein embeddings for machine learning

(2018) Kevin K Yang et al.   BIOINFORMATICS

A statistical model for improved membrane protein expression using sequence-derived features

(2018) Shyam M. Saladi et al.   JOURNAL OF BIOLOGICAL CHEMISTRY

Recurrent Neural Network Model for Constructive Peptide Design

(2018) Alex T. Müller et al.   Journal of Chemical Information and Modeling

Improved Descriptors for the Quantitative Structure–Activity Relationship Modeling of Peptides and Proteins

(2018) Mark H. Barley et al.   Journal of Chemical Information and Modeling

Near perfect protein multi-label classification with deep neural networks

(2018) Balázs Szalkai et al.   METHODS

Deep generative models of genetic variation capture the effects of mutations

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

Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins

(2018) Yutaka Saito et al.   ACS Synthetic Biology

Learning epistatic interactions from sequence-activity data to predict enantioselectivity

(2017) Julian Zaugg et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network

(2017) Renzhi Cao et al.   MOLECULES

Sampling and energy evaluation challenges in ligand binding protein design

(2017) Jiayi Dou et al.   PROTEIN SCIENCE

Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization

(2017) Claire N. Bedbrook et al.   PLoS Computational Biology

Convolutional neural network architectures for predicting DNA–protein binding

(2016) Haoyang Zeng et al.   BIOINFORMATICS

UniProt: the universal protein knowledgebase

(2016)   NUCLEIC ACIDS RESEARCH

Exploring sequence-function space of a poplar glutathione transferase using designed information-rich gene variants

(2016) Yaman Musdal et al.   PROTEIN ENGINEERING DESIGN & SELECTION

Semisupervised Gaussian Process for Automated Enzyme Search

(2016) Joseph Mellor et al.   ACS Synthetic Biology

ProFET: Feature engineering captures high-level protein functions

(2015) Dan Ofer et al.   BIOINFORMATICS

Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

(2015) Babak Alipanahi et al.   NATURE BIOTECHNOLOGY

A deep learning framework for modeling structural features of RNA-binding protein targets

(2015) Sai Zhang et al.   NUCLEIC ACIDS RESEARCH

Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools

(2015) Lei Jia et al.   PLoS One

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

(2015) Ehsaneddin Asgari et al.   PLoS One

NeEMO: a method using residue interaction networks to improve prediction of protein stability upon mutation

(2014) Manuel Giollo et al.   BMC GENOMICS

Deep mutational scanning: a new style of protein science

(2014) Douglas M Fowler et al.   NATURE METHODS

Mapping of Amino Acid Substitutions Conferring Herbicide Resistance in Wheat Glutathione Transferase

(2014) Sridhar Govindarajan et al.   ACS Synthetic Biology

mCSM: predicting the effects of mutations in proteins using graph-based signatures

(2013) Douglas E. V. Pires et al.   BIOINFORMATICS

Representation Learning: A Review and New Perspectives

(2013) Y. Bengio et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

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

Grading amino acid properties increased accuracies of single point mutation on protein stability prediction

(2012) Jianguo Liu et al.   BMC BIOINFORMATICS

Three-Dimensional Structures of Membrane Proteins from Genomic Sequencing

(2012) Thomas A. Hopf et al.   CELL

A few useful things to know about machine learning

(2012) Pedro Domingos   COMMUNICATIONS OF THE ACM

PROTS-RF: A Robust Model for Predicting Mutation-Induced Protein Stability Changes

(2012) Yunqi Li et al.   PLoS One

Enzyme Promiscuity: A Mechanistic and Evolutionary Perspective

(2010) Olga Khersonsky and Dan S. Tawfik   Annual Review of Biochemistry

Predicting changes in protein thermostability brought about by single- or multi-site mutations

(2010) Jian Tian et al.   BMC BIOINFORMATICS

An exciting but challenging road ahead for computational enzyme design

(2010) David Baker   PROTEIN SCIENCE

Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0

(2009) Yves Dehouck et al.   BIOINFORMATICS

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Exploring protein fitness landscapes by directed evolution

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

In silico characterization of protein chimeras: Relating sequence and function within the same fold

(2009) Fabian A. Buske et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS