Name
Title | ||
|---|---|---|
S2L-PSIBLAST: a supervised two-layer search framework based on PSI-BLAST for protein remote homology detection |
Abstract | ||
|---|---|---|
Motivation: Protein remote homology detection is a challenging task for the studies of protein evolutionary relationships. PSI-BLAST is an important and fundamental search method for detecting homology proteins. Although many improved versions of PSI-BLAST have been proposed, their performance is limited by the search processes of PSI-BLAST. Results: For further improving the performance of PSI-BLAST for protein remote homology detection, a supervised two-layer search framework based on PSI-BLAST (S2L-PSIBLAST) is proposed. S2L-PSIBLAST consists of a twolevel search: the first-level search provides high-quality search results by using SMI-BLAST framework and double-link strategy to filter the non-homology protein sequences, the second-level search detects more homology proteins by profile-link similarity, and more accurate ranking lists for those detected protein sequences are obtained by learning to rank strategy. Experimental results on the updated version of Structural Classification of Proteins-extended benchmark dataset show that S2L-PSIBLAST not only obviously improves the performance of PSI-BLAST, but also achieves better performance on two improved versions of PSI-BLAST: DELTA-BLAST and PSI-BLASTexB. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1093/bioinformatics/btab472 | BIOINFORMATICS |
DocType | Volume | Issue |
Conference | 37 | 23 |
ISSN | Citations | PageRank |
1367-4803 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaopeng Jin | 1 | 1 | 1.36 |
| Qing Liao | 2 | 37 | 11.60 |
| Bin Liu | 3 | 419 | 33.30 |