Semantic Annotation for Biological Information Retrieval System. (9th February 2015)

• Record Type: Journal Article
• Authors: Oshaiba, Mohamed Marouf Z.; El Houby, Enas M. F.; Salah, Akram
• Other Names: Akutsu Tatsuya Academic Editor.
• Is Part Of: Advances in bioinformatics. Volume 2015(2015)
• Publication Date: 2015-02-09
• Subjects: Bioinformatics -- Periodicals; Bioinformatics; Computational Biology -- Periodicals; Periodicals; 570.285
• DOI: 10.1155/2015/597170
• Languages: English
• ISSNs: 1687-8027

Abstract

Abstract : Online literatures are increasing in a tremendous rate. Biological domain is one of the fast growing domains. Biological researchers face a problem finding what they are searching for effectively and efficiently. The aim of this research is to find documents that contain any combination of biological process and/or molecular function and/or cellular component. This research proposes a framework that helps researchers to retrieve meaningful documents related to their asserted terms based on gene ontology (GO). The system utilizes GO by semantically decomposing it into three subontologies (cellular component, biological process, and molecular function). Researcher has the flexibility to choose searching terms from any combination of the three subontologies. Document annotation is taking a place in this research to create an index of biological terms in documents to speed the searching process. Query expansion is used to infer semantically related terms to asserted terms. It increases the search meaningful results using the term synonyms and term relationships. The system uses a ranking method to order the retrieved documents based on the ranking weights. The proposed system achieves researchers' needs to find documents that fit the asserted terms semantically.