Improved algorithms for the identification of yeast proteins and significant transcrption factor and motif analysis

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dc.contributor.authorSeung-Won Lee-
dc.contributor.authorS E Hong-
dc.contributor.authorKyoo-Yeol Lee-
dc.contributor.authorDoil Choi-
dc.contributor.authorH Jeong-
dc.contributor.authorCheol-Goo Hur-
dc.date.accessioned2017-04-19T09:04:42Z-
dc.date.available2017-04-19T09:04:42Z-
dc.date.issued2006-
dc.identifier.issnI000-0158-
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/7455-
dc.description.abstractWith the rapid development of MS tichnologiesy, the demands for a more sophisticated MS interpretation algorithm haves grown as well. We have developed a new protein fingerprinting method using a binomial distribution, (fBIND). With the fBIND, we improved the performance accuracy of protein fingerprinting up to the maximum 49% (more than MOWSE) and 2% than(at a previous binomial distribution approach studied by of Wool et al.) as compared to the established algorithms. Moreover, we also suggest a the statistical approach to define the significance of transcription factors and motifs in the identified proteins based on the Gene Ontology (GO).-
dc.publisherKorea Soc-Assoc-Inst-
dc.titleImproved algorithms for the identification of yeast proteins and significant transcrption factor and motif analysis-
dc.title.alternativeImproved algorithms for the identification of yeast proteins and significant transcrption factor and motif analysis-
dc.typeArticle-
dc.citation.titleGenomics & Informatics-
dc.citation.number2-
dc.citation.endPage93-
dc.citation.startPage87-
dc.citation.volume4-
dc.contributor.affiliatedAuthorSeung-Won Lee-
dc.contributor.affiliatedAuthorKyoo-Yeol Lee-
dc.contributor.affiliatedAuthorCheol-Goo Hur-
dc.contributor.alternativeName이승원-
dc.contributor.alternativeName홍성의-
dc.contributor.alternativeName이규열-
dc.contributor.alternativeName최도일-
dc.contributor.alternativeName정해영-
dc.contributor.alternativeName허철구-
dc.identifier.bibliographicCitationGenomics & Informatics, vol. 4, no. 2, pp. 87-93-
dc.subject.keywordpeptide mass fingerprinting-
dc.subject.keywordmolecular weight search-
dc.subject.keywordbinomial distribution-
dc.subject.keywordhypergeometric distribution-
dc.subject.localPeptide mass fingerprinting (PMF)-
dc.subject.localpeptide mass fingerprinting-
dc.subject.localmolecular weight search-
dc.subject.localbinomial distribution-
dc.subject.localhypergeometric distribution-
dc.description.journalClassN-
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