Name
Title | ||
|---|---|---|
Protein Fold Recognition by Combining Support Vector Machines and Pairwise Sequence Similarity Scores |
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 the alignment scores between query-template protein pairs and the other is the machine learning method based on the feature representation and classifier. These two ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCBB.2020.2966450 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | DocType | Volume |
Proteins,Support vector machines,Feature extraction,Machine learning,Training,Hidden Markov models,Protein engineering | Journal | 18 |
Issue | ISSN | Citations |
5 | 1545-5963 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |