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Advances in Bioinformatics
Volume 2015, Article ID 597170, 11 pages
http://dx.doi.org/10.1155/2015/597170
Research Article

Semantic Annotation for Biological Information Retrieval System

1Computer Science Department, Faculty of Computers and Information, Cairo University, Dr. Ahmed Zewail Street, Orman, Giza 12613, Egypt
2Engineering Division, Systems & Information Department, National Research Centre, El Buhouth Street, Dokki, Cairo 12311, Egypt

Received 30 June 2014; Revised 17 December 2014; Accepted 19 December 2014

Academic Editor: Tatsuya Akutsu

Copyright © 2015 Mohamed Marouf Z. Oshaiba et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.