A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences.
Abstract: A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to comp...
| Publicado en: | Journal of Biomedical Informatics Vol. 41; no. 1; pp. 65 - 82 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Academic Press Inc.
Feb2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105867685&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105867685 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15320464 OMB jtl: Journal of Biomedical Informatics issn: 15320464 maglogo: N pubinfo: dt: Feb2008 vid: 41 iid: 1 pid: 735 pub: Academic Press Inc. place: Burlington, Massachusetts artinfo: ui: 105867685 2009820940 NLM17681495 105867685 ppf: 65 ppct: 17 formats: tig: atl: A genetic similarity algorithm for searching the Gene Ontology terms and annotating anonymous protein sequences. aug: au: Othman RM Deris S Illias RM sug: subj: Algorithms Genetic Techniques Methods Management Information Systems Proteins Classification Proteins Resource Databases Sequence Analysis Methods Amino Acids Documentation Information Retrieval Methods Information Science Methods Natural Language Processing ab: Abstract: A genetic similarity algorithm is introduced in this study to find a group of semantically similar Gene Ontology terms. The genetic similarity algorithm combines semantic similarity measure algorithm with parallel genetic algorithm. The semantic similarity measure algorithm is used to compute the similitude strength between the Gene Ontology terms. Then, the parallel genetic algorithm is employed to perform batch retrieval and to accelerate the search in large search space of the Gene Ontology graph. The genetic similarity algorithm is implemented in the Gene Ontology browser named basic UTMGO to overcome the weaknesses of the existing Gene Ontology browsers which use a conventional approach based on keyword matching. To show the applicability of the basic UTMGO, we extend its structure to develop a Gene Ontology -based protein sequence annotation tool named extended UTMGO. The objective of developing the extended UTMGO is to provide a simple and practical tool that is capable of producing better results and requires a reasonable amount of running time with low computing cost specifically for offline usage. The computational results and comparison with other related tools are presented to show the effectiveness of the proposed algorithm and tools. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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