Protein remote homology detection and structural alignment using deep learning
Exploiting sequence–structure–function relationships in biotechnology requires improved
methods for aligning proteins that have low sequence similarity to previously annotated …
methods for aligning proteins that have low sequence similarity to previously annotated …
DeepSVM-fold: protein fold recognition by combining support vector machines and pairwise sequence similarity scores generated by deep learning networks
B Liu, CC Li, K Yan - Briefings in bioinformatics, 2020 - academic.oup.com
Protein fold recognition is critical for studying the structures and functions of proteins. The
existing protein fold recognition approaches failed to efficiently calculate the pairwise …
existing protein fold recognition approaches failed to efficiently calculate the pairwise …
Unsupervised protein embeddings outperform hand-crafted sequence and structure features at predicting molecular function
Motivation Protein function prediction is a difficult bioinformatics problem. Many recent
methods use deep neural networks to learn complex sequence representations and predict …
methods use deep neural networks to learn complex sequence representations and predict …
MotifCNN-fold: protein fold recognition based on fold-specific features extracted by motif-based convolutional neural networks
CC Li, B Liu - Briefings in bioinformatics, 2020 - academic.oup.com
Protein fold recognition is one of the most critical tasks to explore the structures and
functions of the proteins based on their primary sequence information. The existing protein …
functions of the proteins based on their primary sequence information. The existing protein …
FoldRec-C2C: protein fold recognition by combining cluster-to-cluster model and protein similarity network
J Shao, K Yan, B Liu - Briefings in bioinformatics, 2021 - academic.oup.com
As a key for studying the protein structures, protein fold recognition is playing an important
role in predicting the protein structures associated with COVID-19 and other important …
role in predicting the protein structures associated with COVID-19 and other important …
Protein fold recognition based on multi-view modeling
Motivation Protein fold recognition has attracted increasing attention because it is critical for
studies of the 3D structures of proteins and drug design. Researchers have been extensively …
studies of the 3D structures of proteins and drug design. Researchers have been extensively …
ProtFold-DFG: protein fold recognition by combining Directed Fusion Graph and PageRank algorithm
J Shao, B Liu - Briefings in Bioinformatics, 2021 - academic.oup.com
As one of the most important tasks in protein structure prediction, protein fold recognition has
attracted more and more attention. In this regard, some computational predictors have been …
attracted more and more attention. In this regard, some computational predictors have been …
Fold-LTR-TCP: protein fold recognition based on triadic closure principle
B Liu, Y Zhu, K Yan - Briefings in Bioinformatics, 2020 - academic.oup.com
As an important task in protein structure and function studies, protein fold recognition has
attracted more and more attention. The existing computational predictors in this field treat …
attracted more and more attention. The existing computational predictors in this field treat …
An analysis of protein language model embeddings for fold prediction
A Villegas-Morcillo, AM Gomez… - Briefings in …, 2022 - academic.oup.com
The identification of the protein fold class is a challenging problem in structural biology.
Recent computational methods for fold prediction leverage deep learning techniques to …
Recent computational methods for fold prediction leverage deep learning techniques to …
Protein threading using residue co-variation and deep learning
Motivation Template-based modeling, including homology modeling and protein threading,
is a popular method for protein 3D structure prediction. However, alignment generation and …
is a popular method for protein 3D structure prediction. However, alignment generation and …