%0 Journal Article %1 leroy.co-occurrence.2005 %A Leroy, Gondy %A Chen, Hsinchun %D 2005 %J JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY %K CAT CAT-REL-COOR CAT-REL-RULE-PP co-occurence genescene ontology-based %N 5 %P 457--468 %T Genescene: An Ontology-Enhanced Integration of Linguistic and Co-Occurrence Based Relations in Biomedical Texts %U http://www.google.com/url?sa=t&source=web&cd=3&ved=0CB4QFjAC&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.124.1805%26rep%3Drep1%26type%3Dpdf&rct=j&q=H%20chen%20u%20of%20arizona%20genescene&ei=IW6BTP_PKpL4swOOlKX4Bw&usg=AFQjCNGWHdSQcFi1QPRRhNuyX_IFINO6Qw&sig2=4eJegPhWWgWjdxYAD0n_2g&cad=rja %V 56 %X The increasing amount of publicly available literature and experimental data in biomedicine makes it hard for biomedical researchers to stay up-to-date. Genescene is a toolkit that will help alleviate this problem by providing an overview of published literature content. We com- bined a linguistic parser with Concept Space, a co- occurrence based semantic net. Both techniques extract complementary biomedical relations between noun phrases from MEDLINE abstracts. The parser extracts precise and semantically rich relations from individual abstracts. Concept Space extracts relations that hold true for the collection of abstracts. The Gene Ontology, the Human Genome Nomenclature, and the Unified Med- ical Language System, are also integrated in Genescene. Currently, they are used to facilitate the integration of the two relation types, and to select the more interesting and high-quality relations for presentation. A user study fo- cusing on p53 literature is discussed. All MEDLINE ab- stracts discussing p53 were processed in Genescene. Two researchers evaluated the terms and relations from several abstracts of interest to them. The results show that the terms were precise (precision 93%) and relevant, as were the parser relations (precision 95%). The Con- cept Space relations were more precise when selected with ontological knowledge (precision 78%) than without (60%).

@article{leroy.co-occurrence.2005, abstract = {The increasing amount of publicly available literature and experimental data in biomedicine makes it hard for biomedical researchers to stay up-to-date. Genescene is a toolkit that will help alleviate this problem by providing an overview of published literature content. We com- bined a linguistic parser with Concept Space, a co- occurrence based semantic net. Both techniques extract complementary biomedical relations between noun phrases from MEDLINE abstracts. The parser extracts precise and semantically rich relations from individual abstracts. Concept Space extracts relations that hold true for the collection of abstracts. The Gene Ontology, the Human Genome Nomenclature, and the Unified Med- ical Language System, are also integrated in Genescene. Currently, they are used to facilitate the integration of the two relation types, and to select the more interesting and high-quality relations for presentation. A user study fo- cusing on p53 literature is discussed. All MEDLINE ab- stracts discussing p53 were processed in Genescene. Two researchers evaluated the terms and relations from several abstracts of interest to them. The results show that the terms were precise (precision 93%) and relevant, as were the parser relations (precision 95%). The Con- cept Space relations were more precise when selected with ontological knowledge (precision 78%) than without (60%).}, added-at = {2010-09-04T00:02:59.000+0200}, author = {Leroy, Gondy and Chen, Hsinchun}, biburl = {https://www.bibsonomy.org/bibtex/2c2a8227fbd70007f00c7ad5ee17d638a/huiyangsfsu}, interhash = {6d481873522e028e7ce5533abf4f3d65}, intrahash = {c2a8227fbd70007f00c7ad5ee17d638a}, journal = {JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY}, keywords = {CAT CAT-REL-COOR CAT-REL-RULE-PP co-occurence genescene ontology-based}, number = 5, pages = {457--468}, timestamp = {2010-11-12T02:31:00.000+0100}, title = {Genescene: An Ontology-Enhanced Integration of Linguistic and Co-Occurrence Based Relations in Biomedical Texts }, url = {http://www.google.com/url?sa=t&source=web&cd=3&ved=0CB4QFjAC&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.124.1805%26rep%3Drep1%26type%3Dpdf&rct=j&q=H%20chen%20u%20of%20arizona%20genescene&ei=IW6BTP_PKpL4swOOlKX4Bw&usg=AFQjCNGWHdSQcFi1QPRRhNuyX_IFINO6Qw&sig2=4eJegPhWWgWjdxYAD0n_2g&cad=rja}, volume = 56, year = 2005 }