[HTML][HTML] Deep learning methods in protein structure prediction
M Torrisi, G Pollastri, Q Le - Computational and Structural Biotechnology …, 2020 - Elsevier
Abstract Protein Structure Prediction is a central topic in Structural Bioinformatics. Since
the'60s statistical methods, followed by increasingly complex Machine Learning and recently …
the'60s statistical methods, followed by increasingly complex Machine Learning and recently …
Deep mutational scanning: a new style of protein science
Mutagenesis provides insight into proteins, but only recently have assays that couple
genotype to phenotype been used to assess the activities of as many as 1 million mutant …
genotype to phenotype been used to assess the activities of as many as 1 million mutant …
Evaluating protein transfer learning with TAPE
Protein modeling is an increasingly popular area of machine learning research. Semi-
supervised learning has emerged as an important paradigm in protein modeling due to the …
supervised learning has emerged as an important paradigm in protein modeling due to the …
Machine learning-assisted directed protein evolution with combinatorial libraries
To reduce experimental effort associated with directed protein evolution and to explore the
sequence space encoded by mutating multiple positions simultaneously, we incorporate …
sequence space encoded by mutating multiple positions simultaneously, we incorporate …
Accurate de novo prediction of protein contact map by ultra-deep learning model
Motivation Protein contacts contain key information for the understanding of protein structure
and function and thus, contact prediction from sequence is an important problem. Recently …
and function and thus, contact prediction from sequence is an important problem. Recently …
Protein structure determination using metagenome sequence data
Despite decades of work by structural biologists, there are still~ 5200 protein families with
unknown structure outside the range of comparative modeling. We show that Rosetta …
unknown structure outside the range of comparative modeling. We show that Rosetta …
Assessment of contact predictions in CASP12: co‐evolution and deep learning coming of age
J Schaarschmidt, B Monastyrskyy… - Proteins: Structure …, 2018 - Wiley Online Library
Following up on the encouraging results of residue‐residue contact prediction in the
CASP11 experiment, we present the analysis of predictions submitted for CASP12. The …
CASP11 experiment, we present the analysis of predictions submitted for CASP12. The …
High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features
DT Jones, SM Kandathil - Bioinformatics, 2018 - academic.oup.com
Motivation In addition to substitution frequency data from protein sequence alignments,
many state-of-the-art methods for contact prediction rely on additional sources of …
many state-of-the-art methods for contact prediction rely on additional sources of …
Large-scale determination of previously unsolved protein structures using evolutionary information
The prediction of the structures of proteins without detectable sequence similarity to any
protein of known structure remains an outstanding scientific challenge. Here we report …
protein of known structure remains an outstanding scientific challenge. Here we report …
Three-dimensional protein structure prediction: Methods and computational strategies
A long standing problem in structural bioinformatics is to determine the three-dimensional (3-
D) structure of a protein when only a sequence of amino acid residues is given. Many …
D) structure of a protein when only a sequence of amino acid residues is given. Many …