CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction

Improved protein structure prediction using potentials from deep learning

(2020) Andrew W. Senior et al.   NATURE

Improved protein structure prediction using predicted interresidue orientations

(2020) Jianyi Yang et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Advances in protein structure prediction and design

(2019) Brian Kuhlman et al.   NATURE REVIEWS MOLECULAR CELL BIOLOGY

Distance-based protein folding powered by deep learning

(2019) Jinbo Xu   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins

(2019) Chengxin Zhang et al.   BIOINFORMATICS

Detecting distant-homology protein structures by aligning deep neural-network based contact maps

(2019) Wei Zheng et al.   PLoS Computational Biology

Protein threading using residue co-variation and deep learning

(2018) Jianwei Zhu et al.   BIOINFORMATICS

Clustering huge protein sequence sets in linear time

(2018) Martin Steinegger et al.   Nature Communications

Uniclust databases of clustered and deeply annotated protein sequences and alignments

(2016) Milot Mirdita et al.   NUCLEIC ACIDS RESEARCH

CATH: an expanded resource to predict protein function through structure and sequence

(2016) Natalie L. Dawson et al.   NUCLEIC ACIDS RESEARCH

The I-TASSER Suite: protein structure and function prediction

(2015) Jianyi Yang et al.   NATURE METHODS

CCMpred—fast and precise prediction of protein residue–residue contacts from correlated mutations

(2014) Stefan Seemayer et al.   BIOINFORMATICS

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

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

Emerging methods in protein co-evolution

(2013) David de Juan et al.   NATURE REVIEWS GENETICS

Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models

(2013) Magnus Ekeberg et al.   PHYSICAL REVIEW E

Protein structure prediction from sequence variation

(2012) Debora S Marks et al.   NATURE BIOTECHNOLOGY

The Protein-Folding Problem, 50 Years On

(2012) K. A. Dill et al.   SCIENCE

PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments

(2011) David T. Jones et al.   BIOINFORMATICS

Protein 3D Structure Computed from Evolutionary Sequence Variation

(2011) Debora S. Marks et al.   PLoS One

Direct-coupling analysis of residue coevolution captures native contacts across many protein families

(2011) F. Morcos et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta

(2010) S. Chaudhury et al.   BIOINFORMATICS

I-TASSER: a unified platform for automated protein structure and function prediction

(2010) Ambrish Roy et al.   Nature Protocols

Identification of direct residue contacts in protein-protein interaction by message passing

(2008) M. Weigt et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction

(2002) Hongyi Zhou et al.   PROTEIN SCIENCE