Approximate subgraph matching-based literature mining for biomedical events and relations.
The biomedical text mining community has focused on developing techniques to automatically extract important relations between biological components and semantic events involving genes or proteins from literature. In this paper, we propose a novel approach for mining relations and events in the biom...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2013-01-01
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| Series: | PLoS ONE |
| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23613763/pdf/?tool=EBI |
| _version_ | 1818458928980164608 |
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| author | Haibin Liu Lawrence Hunter Vlado Kešelj Karin Verspoor |
| author_facet | Haibin Liu Lawrence Hunter Vlado Kešelj Karin Verspoor |
| author_sort | Haibin Liu |
| collection | DOAJ |
| description | The biomedical text mining community has focused on developing techniques to automatically extract important relations between biological components and semantic events involving genes or proteins from literature. In this paper, we propose a novel approach for mining relations and events in the biomedical literature using approximate subgraph matching. Extraction of such knowledge is performed by searching for an approximate subgraph isomorphism between key contextual dependencies and input sentence graphs. Our approach significantly increases the chance of retrieving relations or events encoded within complex dependency contexts by introducing error tolerance into the graph matching process, while maintaining the extraction precision at a high level. When evaluated on practical tasks, it achieves a 51.12% F-score in extracting nine types of biological events on the GE task of the BioNLP-ST 2011 and an 84.22% F-score in detecting protein-residue associations. The performance is comparable to the reported systems across these tasks, and thus demonstrates the generalizability of our proposed approach. |
| first_indexed | 2024-12-14T23:06:15Z |
| format | Article |
| id | doaj.art-995f7980536a4081ba98d97a1934f428 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-14T23:06:15Z |
| publishDate | 2013-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-995f7980536a4081ba98d97a1934f4282022-12-21T22:44:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0184e6095410.1371/journal.pone.0060954Approximate subgraph matching-based literature mining for biomedical events and relations.Haibin LiuLawrence HunterVlado KešeljKarin VerspoorThe biomedical text mining community has focused on developing techniques to automatically extract important relations between biological components and semantic events involving genes or proteins from literature. In this paper, we propose a novel approach for mining relations and events in the biomedical literature using approximate subgraph matching. Extraction of such knowledge is performed by searching for an approximate subgraph isomorphism between key contextual dependencies and input sentence graphs. Our approach significantly increases the chance of retrieving relations or events encoded within complex dependency contexts by introducing error tolerance into the graph matching process, while maintaining the extraction precision at a high level. When evaluated on practical tasks, it achieves a 51.12% F-score in extracting nine types of biological events on the GE task of the BioNLP-ST 2011 and an 84.22% F-score in detecting protein-residue associations. The performance is comparable to the reported systems across these tasks, and thus demonstrates the generalizability of our proposed approach.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23613763/pdf/?tool=EBI |
| spellingShingle | Haibin Liu Lawrence Hunter Vlado Kešelj Karin Verspoor Approximate subgraph matching-based literature mining for biomedical events and relations. PLoS ONE |
| title | Approximate subgraph matching-based literature mining for biomedical events and relations. |
| title_full | Approximate subgraph matching-based literature mining for biomedical events and relations. |
| title_fullStr | Approximate subgraph matching-based literature mining for biomedical events and relations. |
| title_full_unstemmed | Approximate subgraph matching-based literature mining for biomedical events and relations. |
| title_short | Approximate subgraph matching-based literature mining for biomedical events and relations. |
| title_sort | approximate subgraph matching based literature mining for biomedical events and relations |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23613763/pdf/?tool=EBI |
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