DocumentCode :
2830150
Title :
Comprehensive Gene Ontology Mapping Strategies for Improved Biological Inference
Author :
Xu, Qing-Wei ; Yang, Li ; Li, Jiang
Author_Institution :
Comput. Sci. & Technol., HUBEI Univ. of Educ., Wuhan, China
fYear :
2009
fDate :
11-12 July 2009
Firstpage :
66
Lastpage :
69
Abstract :
Lack of sufficient semantic relationships between pairs of terms coming from the three independent gene ontology sub-ontologies, that limit the power to provide complex semantic queries and inference services based on it. By integrating non-lexical and lexical learning strategies into GLUE system, we semi-automatically generate six types of one-to-one mapping paths covered almost half of all GO terms. We believe that the comprehensive ontology mapping strategies might be an effective way to bridge the gap between non-lexical and lexical approaches, as well as improve accuracy and coverage.
Keywords :
biology computing; genetics; inference mechanisms; ontologies (artificial intelligence); GLUE system; biological inference; gene ontology mapping; lexical learning strategy; Biological processes; Biology; Bridges; Chemical technology; Computer science; Computer science education; Databases; Educational technology; Ontologies; Organisms; GLUE System; Gene Ontology; Ontology Mapping;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems Engineering, 2009. CASE 2009. IITA International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-0-7695-3728-3
Type :
conf
DOI :
10.1109/CASE.2009.103
Filename :
5194392
Link To Document :
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