[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 …

Deep learning in protein structural modeling and design

W Gao, SP Mahajan, J Sulam, JJ Gray - Patterns, 2020 - cell.com
Deep learning is catalyzing a scientific revolution fueled by big data, accessible toolkits, and
powerful computational resources, impacting many fields, including protein structural …

Improved protein structure prediction using potentials from deep learning

AW Senior, R Evans, J Jumper, J Kirkpatrick, L Sifre… - Nature, 2020 - nature.com
Protein structure prediction can be used to determine the three-dimensional shape of a
protein from its amino acid sequence. This problem is of fundamental importance as the …

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

A Rives, J Meier, T Sercu, S Goyal… - Proceedings of the …, 2021 - National Acad Sciences
In the field of artificial intelligence, a combination of scale in data and model capacity
enabled by unsupervised learning has led to major advances in representation learning and …

Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations

W Zheng, C Zhang, Y Li, R Pearce, EW Bell… - Cell reports methods, 2021 - cell.com
Structure prediction for proteins lacking homologous templates in the Protein Data Bank
(PDB) remains a significant unsolved problem. We developed a protocol, CI-TASSER, to …

MSA transformer

RM Rao, J Liu, R Verkuil, J Meier… - International …, 2021 - proceedings.mlr.press
Unsupervised protein language models trained across millions of diverse sequences learn
structure and function of proteins. Protein language models studied to date have been …

The PSIPRED protein analysis workbench: 20 years on

DWA Buchan, DT Jones - Nucleic acids research, 2019 - academic.oup.com
The PSIPRED Workbench is a web server offering a range of predictive methods to the
bioscience community for 20 years. Here, we present the work we have completed to update …

High-resolution de novo structure prediction from primary sequence

R Wu, F Ding, R Wang, R Shen, X Zhang, S Luo, C Su… - BioRxiv, 2022 - biorxiv.org
Recent breakthroughs have used deep learning to exploit evolutionary information in
multiple sequence alignments (MSAs) to accurately predict protein structures. However …

Evaluating protein transfer learning with TAPE

R Rao, N Bhattacharya, N Thomas… - Advances in neural …, 2019 - proceedings.neurips.cc
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 …

Accurate de novo prediction of protein contact map by ultra-deep learning model

S Wang, S Sun, Z Li, R Zhang, J Xu - PLoS computational biology, 2017 - journals.plos.org
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 …