Name
Title | ||
|---|---|---|
Sequence-based prediction of physicochemical interactions at protein functional sites using a function-and-interaction-annotated domain profile database. |
Abstract | ||
|---|---|---|
Our results show that, in addition to the PFSs, the physical interactions at these sites are also conserved in the evolution of proteins. This work provides a valuable sequence-based tool for rational drug design and side-effect assessment. The method is freely available and can be accessed at http://202.119.249.49 . |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2206-2 | BMC Bioinformatics |
Keywords | Field | DocType |
Domain profile module,Hidden Markov model,Physicochemical interaction prediction,Protein functional site prediction,fiDPD | Protein domain,Matthews correlation coefficient,Drug design,Biology,Biochemical reactions,Protein Data Bank,Hidden Markov model,Database,DNA microarray | Journal |
Volume | Issue | ISSN |
19 | 1 | 1471-2105 |
Citations | PageRank | References |
0 | 0.34 | 27 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min Han | 1 | 761 | 68.01 |
| Yifan Song | 2 | 0 | 0.68 |
| Jiaqiang Qian | 3 | 1 | 0.69 |
| Dengming Ming | 4 | 0 | 0.34 |