Text-mining research in genomics
| Main Authors: | Gálvez, Carmen, Moya-Anegón, Félix |
|---|---|
| Other Authors: | Guimaraes, Nuno, Isaías, Pedro |
| Format: | Proceeding PeerReviewed application/pdf |
| Bahasa: | eng |
| Terbitan: |
International Association for Development of the Information Society (IADIS)
, 2008
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| Subjects: | |
| Online Access: |
http://eprints.rclis.org/12140/1/Galvez-AC-2008.pdf http://eprints.rclis.org/12140/ |
Daftar Isi:
- Biomedical text-mining have great promise to improve the usefulness of genomic researchers. The goal of text-mining is analyzed large collections of unstructured documents for the purposes of extracting interesting and non-trivial patterns of knowledge. The analysis of biomedical texts and available databases, such as Medline and PubMed, can help to interpret a phenomenon, to detect gene relations, or to establish comparisons among similar genes in different specific databases. All these processes are crucial for making sense of the immense quantity of genomic information. In genomics, text-mining research refers basically to the creation of literature networks of related biological entities. Text data represent the genomics knowledge base and can be mined for relationships, literature networks, and new discoveries by literature relational chaining. However, text-mining is an emerging field without a clear definition in the genomics. This work presents some applications of text-mining to genome-based research, such as the genomic term identification in curation processes, the formulation of hypotheses about disease, the visualization of biological relationships, or the life-science domain mapping.