| A text-mining perspective on the requirements for electronically annotated abstracts. | |
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MedLine Citation:
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PMID: 18328824 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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We propose that the combination of human expertise and automatic text-mining systems can be used to create a first generation of electronically annotated information (EAI) that can be added to journal abstracts and that is directly related to the information in the corresponding text. The first experiments have concentrated on the annotation of gene/protein names and those of organisms, as these are the best resolved problems. A second generation of systems could then attempt to address the problems of annotating protein interactions and protein/gene functions, a more difficult task for text-mining systems. EAI will permit easier categorization of this information, it will help in the evaluation of papers for their curation in databases, and it will be invaluable for maintaining the links between the information in databases and the facts described in text. Additionally, it will contribute to the efforts towards completing database information and creating collections of annotated text that can be used to train new generations of text-mining systems. The recent introduction of the first meta-server for the annotation of biological text, with the possibility of collecting annotations from available text-mining systems, adds credibility to the technical feasibility of this proposal. |
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Authors:
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Florian Leitner; Alfonso Valencia |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't; Review Date: 2008-03-06 |
Journal Detail:
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Title: FEBS letters Volume: 582 ISSN: 0014-5793 ISO Abbreviation: FEBS Lett. Publication Date: 2008 Apr |
Date Detail:
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Created Date: 2008-04-03 Completed Date: 2008-08-04 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0155157 Medline TA: FEBS Lett Country: Netherlands |
Other Details:
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Languages: eng Pagination: 1178-81 Citation Subset: IM |
Affiliation:
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Structural Computational Biology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Information Storage and Retrieval* Publishing* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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