Structural protein fold recognition based on secondary structure and evolutionary information using machine learning algorithms
Sign Up to like & getrecommendations! Published in 2021 at "Computational biology and chemistry"
DOI: 10.1016/j.compbiolchem.2021.107456
Abstract: Understanding the function of protein is conducive to research in advanced fields such as gene therapy of diseases, the development and design of new drugs, etc. The prerequisite for understanding the function of a protein… read more here.
Keywords: protein; machine learning; fold recognition; structure ... See more keywords
Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of theoretical biology"
DOI: 10.1016/j.jtbi.2017.03.023
Abstract: Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the… read more here.
Keywords: features protein; protein fold; protein sequences; fold recognition ... See more keywords
Learning Protein Embedding to Improve Protein Fold Recognition Using Deep Metric Learning
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00959
Abstract: Protein fold recognition refers to predicting the most likely fold type of the query protein and is a critical step of protein structure and function prediction. With the popularity of deep learning in bioinformatics, protein… read more here.
Keywords: fold recognition; improve protein; protein fold; deep metric ... See more keywords
A novel fusion based on the evolutionary features for protein fold recognition using support vector machines
Sign Up to like & getrecommendations! Published in 2020 at "Scientific Reports"
DOI: 10.1038/s41598-020-71172-x
Abstract: Protein fold recognition plays a crucial role in discovering three-dimensional structure of proteins and protein functions. Several approaches have been employed for the prediction of protein folds. Some of these approaches are based on extracting… read more here.
Keywords: information; support vector; features protein; protein fold ... See more keywords
DeepSF: deep convolutional neural network for mapping protein sequences to folds
Sign Up to like & getrecommendations! Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btx780
Abstract: Motivation Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a target protein based on the fold of… read more here.
Keywords: protein; protein sequences; fold recognition; neural network ... See more keywords
Protein fold recognition based on multi-view modeling
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btz040
Abstract: 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 studying this important task, and several features with… read more here.
Keywords: fold fold; protein fold; recognition; fold recognition ... See more keywords
Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores
Sign Up to like & getrecommendations! Published in 2021 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2020.2966450
Abstract: Protein fold recognition is one of the most essential steps for protein structure prediction, aiming to classify proteins into known protein folds. There are two main computational approaches: one is the template-based method based on… read more here.
Keywords: support vector; tsvm fold; protein fold; vector machines ... See more keywords