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