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dc.contributor.authorMohabatkar, H.
dc.coverage.spatialIranen_US
dc.date.accessioned2018-03-10T21:10:41Z
dc.date.available2018-03-10T21:10:41Z
dc.date.issued2005
dc.identifier.issn1026-1354
dc.identifier.urihttp://hdl.handle.net/1834/12316
dc.description.abstractWhite spot syndrome is one of the major problems in shrimp culture worldwide. There are different techniques like Dot blotting, PCR and using monoclonal antibodies for diagnosis of White Spot Syndrome Virus (WSSV). in the latter method, by using laboratory animals, monoclonal antibodies against different antigenic domains of proteins of the virus are developed. Then the reactivity of these antibodies with all proteins of shrimp can be tested by ELISA. As it is not known at the start of the test which parts of a protein are strong epitopes and so there is a need to test many peptides, this method is expensive and time consuming. One of the solutions for this problem is prediction of epitopes, synthesis of few peptides, and testing these peptides. Since VP28 is the most important protein of WSSV capsid, the sequences of amino acids of VP28 of four isolates of WSSV from different parts of the world were collected for this study. By using bioinformatic methods, after aligning of sequences the consensus sequence was identified. For prediction of antigenic domains of V28, seven different programs were used. The analysis through the computer programme resulted in prediction of five epitopes in V28. These parts of the protein can now be synthesized and tested for identification of the virus.en_US
dc.language.isofaen_US
dc.relation.urihttp://isfj.areo.ir/en_US
dc.subject.otherWhite Spot Syndromeen_US
dc.subject.otherShrimp cultureen_US
dc.titleApplication of bioinformatics in diagnosis of White Spot Syndrome Virusen_US
dc.typeJournal Contributionen_US
dc.bibliographicCitation.issue1en_US
dc.bibliographicCitation.titleIranian Scientific Fisheries Journalen_US
dc.bibliographicCitation.volume14en_US
dc.description.statusPublisheden_US
dc.format.pagerangepp.177-182en_US
dc.subject.asfaBioinformaticsen_US
dc.subject.asfaEpitopeen_US
dc.subject.asfaWSSVen_US
dc.subject.asfaIdentificationen_US
dc.type.refereedRefereeden_US
refterms.dateFOA2021-01-30T18:48:27Z


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