[HTML][HTML] Deep learning for protein secondary structure prediction: Pre and post-AlphaFold
DP Ismi, R Pulungan - Computational and structural biotechnology …, 2022 - Elsevier
This paper aims to provide a comprehensive review of the trends and challenges of deep
neural networks for protein secondary structure prediction (PSSP). In recent years, deep …
neural networks for protein secondary structure prediction (PSSP). In recent years, deep …
Reaching alignment-profile-based accuracy in predicting protein secondary and tertiary structural properties without alignment
Protein language models have emerged as an alternative to multiple sequence alignment
for enriching sequence information and improving downstream prediction tasks such as …
for enriching sequence information and improving downstream prediction tasks such as …
Recent advances in computational prediction of secondary and supersecondary structures from protein sequences
The secondary structures (SSs) and supersecondary structures (SSSs) underlie the three-
dimensional structure of proteins. Prediction of the SSs and SSSs from protein sequences …
dimensional structure of proteins. Prediction of the SSs and SSSs from protein sequences …
SPOT-1D-Single: improving the single-sequence-based prediction of protein secondary structure, backbone angles, solvent accessibility and half-sphere exposures …
Motivation Knowing protein secondary and other one-dimensional structural properties are
essential for accurate protein structure and function prediction. As a result, many methods …
essential for accurate protein structure and function prediction. As a result, many methods …
OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors
G Xu, Q Wang, J Ma - Briefings in Bioinformatics, 2022 - academic.oup.com
Accurate protein side-chain modeling is crucial for protein folding and protein design. In the
past decades, many successful methods have been proposed to address this issue …
past decades, many successful methods have been proposed to address this issue …
Naive prediction of protein backbone phi and psi dihedral angles using deep learning
M Broz, M Jukič, U Bren - Molecules, 2023 - mdpi.com
Protein structure prediction represents a significant challenge in the field of bioinformatics,
with the prediction of protein structures using backbone dihedral angles recently achieving …
with the prediction of protein structures using backbone dihedral angles recently achieving …
Deep metric learning for accurate protein secondary structure prediction
Predicting the secondary structure of a protein from its amino acid sequence alone is a
challenging prediction task for each residue in bioinformatics. Recent work has mainly used …
challenging prediction task for each residue in bioinformatics. Recent work has mainly used …
RNA backbone torsion and pseudotorsion angle prediction using dilated convolutional neural networks
RNA three-dimensional structure prediction has been relied on using a predicted or
experimentally determined secondary structure as a restraint to reduce the conformational …
experimentally determined secondary structure as a restraint to reduce the conformational …
DLBLS_SS: protein secondary structure prediction using deep learning and broad learning system
L Yuan, X Hu, Y Ma, Y Liu - RSC advances, 2022 - pubs.rsc.org
Protein secondary structure prediction (PSSP) is not only beneficial to the study of protein
structure and function but also to the development of drugs. As a challenging task in …
structure and function but also to the development of drugs. As a challenging task in …
IGPRED: Combination of convolutional neural and graph convolutional networks for protein secondary structure prediction
There is a close relationship between the tertiary structure and the function of a protein. One
of the important steps to determine the tertiary structure is protein secondary structure …
of the important steps to determine the tertiary structure is protein secondary structure …