textpresso an ontology-based information retrieval and extraction system for biological literaturetextpresso生物文学一个基于本体的信息检索和提取系统.pdfVIP

Open access, freely available online PLoS BIOLOGY Textpresso: An Ontology-Based Information Retrieval and Extraction System for Biological Literature ¨ Hans-Michael Muller, Eimear E. Kenny, Paul W. Sternberg* Division of Biology and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California, United States of America We have developed Textpresso, a new text-mining system for scientific literature whose capabilities go far beyond those of a simple keyword search engine. Textpresso’s two major elements are a collection of the full text of scientific articles split into individual sentences, and the implementation of categories of terms for which a database of articles and individual sentences can be searched. The categories are classes of biological concepts (e.g., gene, allele, cell or cell group, phenotype, etc.) and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., biological process, etc.). Together they form a catalog of types of objects and concepts called an ontology. After this ontology is populated with terms, the whole corpus of articles and abstracts is marked up to identify terms of these categories. The current ontology comprises 33 categories of terms. A search engine enables the user to search for one or a combination of these tags and/or keywords within a sentence or document, and as the ontology allows word meaning to be queried, it is possible to formulate semantic queries. Full text access increases recall of biological data types from 45% to 95%. Extraction of particular biological facts, such as gene-gene interactions, can be accelerated significantly by ontologies, with Textpresso automatically performing nearly as well as expert curators to identify sentences; in searches for two uniquel