Name
Title | ||
|---|---|---|
ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature. |
Abstract | ||
|---|---|---|
ECPred is presented both as a stand-alone and a web based tool to provide probabilistic enzymatic function predictions (at all five levels of EC) for uncharacterized protein sequences. Also, the datasets of this study will be a valuable resource for future benchmarking studies. ECPred is available for download, together with all of the datasets used in this study, at: https://github.com/cansyl/ECPred . ECPred webserver can be accessed through http://cansyl.metu.edu.tr/ECPred.html . |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2368-y | BMC Bioinformatics |
Keywords | Field | DocType |
Benchmark datasets,EC numbers,Function prediction,Machine learning,Protein sequence | Enzyme,Biology,Protein sequencing,Enzyme Commission,Nomenclature,Computational biology,Hierarchy,Genetics,DNA microarray | Journal |
Volume | Issue | ISSN |
19 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.34 | 17 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alperen Dalkiran | 1 | 1 | 0.34 |
| Ahmet Süreyya Rifaioglu | 2 | 10 | 1.14 |
| Maria Jesus Martin | 3 | 2793 | 365.41 |
| Rengül Çetin-Atalay | 4 | 20 | 4.11 |
| Volkan Atalay | 5 | 252 | 25.54 |
| Tunca Dogan | 6 | 21 | 3.00 |