ProteinGCN: Protein model quality assessment using graph convolutional networks
Blind estimation of local (per-residue) and global (for the whole structure) accuracies in
protein structure models is an essential step in many protein modeling applications. With the …
protein structure models is an essential step in many protein modeling applications. With the …
3D-equivariant graph neural networks for protein model quality assessment
Motivation Quality assessment (QA) of predicted protein tertiary structure models plays an
important role in ranking and using them. With the recent development of deep learning end …
important role in ranking and using them. With the recent development of deep learning end …
[HTML][HTML] DeepQA: improving the estimation of single protein model quality with deep belief networks
Background Protein quality assessment (QA) useful for ranking and selecting protein models
has long been viewed as one of the major challenges for protein tertiary structure prediction …
has long been viewed as one of the major challenges for protein tertiary structure prediction …
Deep transfer learning in the assessment of the quality of protein models
DM Hurtado, K Uziela, A Elofsson - arXiv preprint arXiv:1804.06281, 2018 - arxiv.org
MOTIVATION: Proteins fold into complex structures that are crucial for their biological
functions. Experimental determination of protein structures is costly and therefore limited to a …
functions. Experimental determination of protein structures is costly and therefore limited to a …
[HTML][HTML] Protein model accuracy estimation based on local structure quality assessment using 3D convolutional neural network
R Sato, T Ishida - PloS one, 2019 - journals.plos.org
In protein tertiary structure prediction, model quality assessment programs (MQAPs) are
often used to select the final structural models from a pool of candidate models generated by …
often used to select the final structural models from a pool of candidate models generated by …
Deep convolutional neural networks for predicting the quality of single protein structural models
Predicting the global quality and local (residual-specific) quality of a single protein structural
model is important for protein structure prediction and application. In this work, we …
model is important for protein structure prediction and application. In this work, we …
AngularQA: protein model quality assessment with LSTM networks
Quality Assessment (QA) plays an important role in protein structure prediction. Traditional
multimodel QA method usually suffer from searching databases or comparing with other …
multimodel QA method usually suffer from searching databases or comparing with other …
Protein model quality assessment using 3D oriented convolutional neural networks
Motivation Protein model quality assessment (QA) is a crucial and yet open problem in
structural bioinformatics. The current best methods for single-model QA typically combine …
structural bioinformatics. The current best methods for single-model QA typically combine …
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 …
[HTML][HTML] Protein model accuracy estimation empowered by deep learning and inter-residue distance prediction in CASP14
The inter-residue contact prediction and deep learning showed the promise to improve the
estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein …
estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein …