![[feed]](/style/images/feed-icon-14x14.png){kind=icon}
Tools
Tools
Preview |
PDF (Original Article)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB |
Preview |
PDF (Supplementary Information)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
313kB |
| Item Type: | Article |
|---|---|
| Title: | PEDL+: Protein-centered relation extraction from PubMed at your fingertip |
| Creators Name: | Weber, L., Barth, F., Lorenz, L., Konrath, F., Huska, K., Wolf, J. and Leser, U. |
| Abstract: | Relation extraction (RE) from large text collections is an important tool for database curation, pathway reconstruction, or functional omics data analysis. In practice, RE often is part of a complex data analysis pipeline requiring specific adaptations like restricting the types of relations or the set of proteins to be considered. However, current systems are either non-programmable web sites or research code with fixed functionality. We present PEDL+, a user-friendly tool for extracting protein-protein and protein-chemical associations from PubMed articles. PEDL+ combines state-of-the-art NLP technology with adaptable ranking and filtering options and can easily be integrated into analysis pipelines. We evaluated PEDL+ in two pathway curation projects and found that 59% to 80% of its extractions were helpful. |
| Keywords: | Factual Databases, PubMed, Software |
| Source: | Bioinformatics |
| ISSN: | 1367-4803 |
| Publisher: | Oxford University Press |
| Volume: | 39 |
| Number: | 11 |
| Page Range: | btad603 |
| Date: | November 2023 |
| Official Publication: | https://doi.org/10.1093/bioinformatics/btad603 |
| PubMed: | View item in PubMed |
Repository Staff Only: item control page
