Ensembling multiple raw coevolutionary features with deep residual neural networks for contact‐map prediction in CASP13

ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks

(2019) Yang Li et al.   BIOINFORMATICS

High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features

(2018) David T Jones et al.   BIOINFORMATICS

Clustering huge protein sequence sets in linear time

(2018) Martin Steinegger et al.   Nature Communications

Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks

(2018) Yang Liu et al.   Cell Systems

Improved protein contact predictions with the MetaPSICOV2 server in CASP12

(2017) Daniel W A Buchan et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12

(2017) Chengxin Zhang et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Assessment of hard target modeling in CASP12 reveals an emerging role of alignment-based contact prediction methods

(2017) Luciano A. Abriata et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Protein structure determination using metagenome sequence data

(2017) Sergey Ovchinnikov et al.   SCIENCE

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

(2017) Sheng Wang et al.   PLoS Computational Biology

Uniclust databases of clustered and deeply annotated protein sequences and alignments

(2016) Milot Mirdita et al.   NUCLEIC ACIDS RESEARCH

Evaluation of free modeling targets in CASP11 and ROLL

(2016) Lisa N. Kinch et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta

(2016) Sergey Ovchinnikov et al.   PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS

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

(2014) Stefan Seemayer et al.   BIOINFORMATICS

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins

(2014) David T. Jones et al.   BIOINFORMATICS

XSEDE: Accelerating Scientific Discovery

(2014) John Towns et al.   COMPUTING IN SCIENCE & ENGINEERING

Fast pseudolikelihood maximization for direct-coupling analysis of protein structure from many homologous amino-acid sequences

(2014) Magnus Ekeberg et al.   JOURNAL OF COMPUTATIONAL PHYSICS

ThreaDom: extracting protein domain boundary information from multiple threading alignments

(2013) Zhidong Xue et al.   BIOINFORMATICS

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

(2013) Magnus Ekeberg et al.   PHYSICAL REVIEW E

Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era

(2013) H. Kamisetty et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

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

(2011) David T. Jones et al.   BIOINFORMATICS

HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment

(2011) Michael Remmert et al.   NATURE METHODS

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

Improving Protein Structure Prediction Using Multiple Sequence-Based Contact Predictions

(2011) Sitao Wu et al.   STRUCTURE

Accelerated Profile HMM Searches

(2011) Sean R. Eddy   PLoS Computational Biology