Name
Title | ||
|---|---|---|
Smi-Blast: A Novel Supervised Search Framework Based On Psi-Blast For Protein Remote Homology Detection |
Abstract | ||
|---|---|---|
Motivation: As one of the most important and widely used mainstream iterative search tool for protein sequence search, an accurate Position-Specific Scoring Matrix (PSSM) is the key of PSI-BLAST. However, PSSMs containing non-homologous information obviously reduce the performance of PSI-BLAST for protein remote homology.Results: To further study this problem, we summarize three types of Incorrectly Selected Homology (ISH) errors in PSSMs. A new search tool Supervised-Manner-based Iterative BLAST (SMI-BLAST) is proposed based on PSIBLAST for solving these errors. SMI-BLAST obviously outperforms PSI-BLAST on the Structural Classification of Proteins-extended (SCOPe) dataset. Compared with PSI-BLAST on the ISH error subsets of SCOPe dataset, SMIBLAST detects 1.6-2.87 folds more remote homologous sequences, and outperforms PSI-BLAST by 35.66% in terms of ROC1 scores. Furthermore, this framework is applied to JackHMMER, DELTA-BLAST and PSI-BLASTexB, and their performance is further improved. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1093/bioinformatics/btaa772 | BIOINFORMATICS |
DocType | Volume | Issue |
Journal | 37 | 7 |
ISSN | Citations | PageRank |
1367-4803 | 1 | 0.35 |
References | Authors | |
0 | 5 | |