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Semantic Annotation for Biological Information Retrieval System

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 biologica...

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Detalles Bibliográficos
Autores principales: Oshaiba, Mohamed Marouf Z., El Houby, Enas M. F., Salah, Akram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4337267/
https://www.ncbi.nlm.nih.gov/pubmed/25737720
http://dx.doi.org/10.1155/2015/597170
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author Oshaiba, Mohamed Marouf Z.
El Houby, Enas M. F.
Salah, Akram
author_facet Oshaiba, Mohamed Marouf Z.
El Houby, Enas M. F.
Salah, Akram
author_sort Oshaiba, Mohamed Marouf Z.
collection PubMed
description 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.
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spelling pubmed-43372672015-03-03 Semantic Annotation for Biological Information Retrieval System Oshaiba, Mohamed Marouf Z. El Houby, Enas M. F. Salah, Akram Adv Bioinformatics Research Article 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. Hindawi Publishing Corporation 2015 2015-02-09 /pmc/articles/PMC4337267/ /pubmed/25737720 http://dx.doi.org/10.1155/2015/597170 Text en Copyright © 2015 Mohamed Marouf Z. Oshaiba et al. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Research Article
Oshaiba, Mohamed Marouf Z.
El Houby, Enas M. F.
Salah, Akram
Semantic Annotation for Biological Information Retrieval System
title Semantic Annotation for Biological Information Retrieval System
title_full Semantic Annotation for Biological Information Retrieval System
title_fullStr Semantic Annotation for Biological Information Retrieval System
title_full_unstemmed Semantic Annotation for Biological Information Retrieval System
title_short Semantic Annotation for Biological Information Retrieval System
title_sort semantic annotation for biological information retrieval system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4337267/
https://www.ncbi.nlm.nih.gov/pubmed/25737720
http://dx.doi.org/10.1155/2015/597170
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