Name
Abstract | ||
|---|---|---|
Motivation: Finding protein-protein interaction (PPI) information from literature is challenging but an important issue. However, keyword search in PubMed (R) is often time consuming because it requires a series of actions that refine keywords and browse search results until it reaches a goal. Due to the rapid growth of biomedical literature, it has become more difficult for biologists and curators to locate PPI information quickly. Therefore, a tool for prioritizing PPI informative articles can be a useful assistant for finding this PPI-relevant information. Results: PIE (Protein Interaction information Extraction) the search is a web service implementing a competition-winning approach utilizing word and syntactic analyses by machine learning techniques. For easy user access, PIE the search provides a PubMed-like search environment, but the output is the list of articles prioritized by PPI confidence scores. By obtaining PPI-related articles at high rank, researchers can more easily find the up-to-date PPI information, which cannot be found in manually curated PPI databases. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1093/bioinformatics/btr702 | BIOINFORMATICS |
Keywords | Field | DocType |
proteins,artificial intelligence | Data mining,World Wide Web,Information retrieval,Computer science,Keyword search,Bioinformatics,Interaction information,Web service,Syntax | Journal |
Volume | Issue | ISSN |
28 | 4 | 1367-4803 |
Citations | PageRank | References |
10 | 0.60 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sun Kim | 1 | 683 | 70.28 |
| Dongseop Kwon | 2 | 193 | 16.67 |
| Soo-Yong Shin | 3 | 196 | 17.20 |
| W John Wilbur | 4 | 267 | 15.23 |