[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 …
Understanding protein non-folding
VN Uversky, AK Dunker - Biochimica et Biophysica Acta (BBA)-Proteins …, 2010 - Elsevier
This review describes the family of intrinsically disordered proteins, members of which fail to
form rigid 3-D structures under physiological conditions, either along their entire lengths or …
form rigid 3-D structures under physiological conditions, either along their entire lengths or …
PredictProtein-predicting protein structure and function for 29 years
Abstract Since 1992 PredictProtein (https://predictprotein. org) is a one-stop online resource
for protein sequence analysis with its main site hosted at the Luxembourg Centre for …
for protein sequence analysis with its main site hosted at the Luxembourg Centre for …
Metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure
Intrinsically disordered proteins and protein regions make up a substantial fraction of many
proteomes in which they play a wide variety of essential roles. A critical first step in …
proteomes in which they play a wide variety of essential roles. A critical first step in …
DISOPRED3: precise disordered region predictions with annotated protein-binding activity
DT Jones, D Cozzetto - Bioinformatics, 2015 - academic.oup.com
Motivation: A sizeable fraction of eukaryotic proteins contain intrinsically disordered regions
(IDRs), which act in unfolded states or by undergoing transitions between structured and …
(IDRs), which act in unfolded states or by undergoing transitions between structured and …
Better prediction of functional effects for sequence variants
Elucidating the effects of naturally occurring genetic variation is one of the major challenges
for personalized health and personalized medicine. Here, we introduce SNAP2, a novel …
for personalized health and personalized medicine. Here, we introduce SNAP2, a novel …
PredictProtein—an open resource for online prediction of protein structural and functional features
G Yachdav, E Kloppmann, L Kajan… - Nucleic acids …, 2014 - academic.oup.com
PredictProtein is a meta-service for sequence analysis that has been predicting structural
and functional features of proteins since 1992. Queried with a protein sequence it returns …
and functional features of proteins since 1992. Queried with a protein sequence it returns …
Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks
Motivation Capturing long-range interactions between structural but not sequence neighbors
of proteins is a long-standing challenging problem in bioinformatics. Recently, long short …
of proteins is a long-standing challenging problem in bioinformatics. Recently, long short …
PONDR-FIT: a meta-predictor of intrinsically disordered amino acids
Protein intrinsic disorder is becoming increasingly recognized in proteomics research. While
lacking structure, many regions of disorder have been associated with biological function …
lacking structure, many regions of disorder have been associated with biological function …
IDP-Seq2Seq: identification of intrinsically disordered regions based on sequence to sequence learning
YJ Tang, YH Pang, B Liu - Bioinformatics, 2020 - academic.oup.com
Motivation Related to many important biological functions, intrinsically disordered regions
(IDRs) are widely distributed in proteins. Accurate prediction of IDRs is critical for the protein …
(IDRs) are widely distributed in proteins. Accurate prediction of IDRs is critical for the protein …