[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 learning-based advances in protein structure prediction
Obtaining an accurate description of protein structure is a fundamental step toward
understanding the underpinning of biology. Although recent advances in experimental …
understanding the underpinning of biology. Although recent advances in experimental …
Learning from protein structure with geometric vector perceptrons
Learning on 3D structures of large biomolecules is emerging as a distinct area in machine
learning, but there has yet to emerge a unifying network architecture that simultaneously …
learning, but there has yet to emerge a unifying network architecture that simultaneously …
Prediction of protein structures, functions and interactions using the IntFOLD7, MultiFOLD and ModFOLDdock servers
LJ McGuffin, NS Edmunds, AG Genc… - Nucleic acids …, 2023 - academic.oup.com
The IntFOLD server based at the University of Reading has been a leading method over the
past decade in providing free access to accurate prediction of protein structures and …
past decade in providing free access to accurate prediction of protein structures and …
GraphQA: protein model quality assessment using graph convolutional networks
Motivation Proteins are ubiquitous molecules whose function in biological processes is
determined by their 3D structure. Experimental identification of a protein's structure can be …
determined by their 3D structure. Experimental identification of a protein's structure can be …
ModFOLD8: accurate global and local quality estimates for 3D protein models
LJ McGuffin, FMF Aldowsari, SMA Alharbi… - Nucleic acids …, 2021 - academic.oup.com
Methods for estimating the quality of 3D models of proteins are vital tools for driving the
acceptance and utility of predicted tertiary structures by the wider bioscience community …
acceptance and utility of predicted tertiary structures by the wider bioscience community …
DeepHomo2. 0: improved protein–protein contact prediction of homodimers by transformer-enhanced deep learning
Protein–protein interactions play an important role in many biological processes. However,
although structure prediction for monomer proteins has achieved great progress with the …
although structure prediction for monomer proteins has achieved great progress with the …
SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model
Motivation Accurate prediction of protein contact-map is essential for accurate protein
structure and function prediction. As a result, many methods have been developed for …
structure and function prediction. As a result, many methods have been developed for …
DeepUMQA: ultrafast shape recognition-based protein model quality assessment using deep learning
Motivation Protein model quality assessment is a key component of protein structure
prediction. In recent research, the voxelization feature was used to characterize the local …
prediction. In recent research, the voxelization feature was used to characterize the local …
Inhibiting a promiscuous GPCR: iterative discovery of bitter taste receptor ligands
F Fierro, L Peri, H Hübner, A Tabor-Schkade… - Cellular and Molecular …, 2023 - Springer
The human GPCR family comprises circa 800 members, activated by hundreds of thousands
of compounds. Bitter taste receptors, TAS2Rs, constitute a large and distinct subfamily …
of compounds. Bitter taste receptors, TAS2Rs, constitute a large and distinct subfamily …