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Improved Algorithms for the Identification of Yeast Proteins and Significant Transcription Factor and Motif Analysis
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  • Improved Algorithms for the Identification of Yeast Proteins and Significant Transcription Factor and Motif Analysis
  • Improved Algorithms for the Identification of Yeast Proteins and Significant Transcription Factor and Motif Analysis
저자명
Lee. Seung-Won,Hong. Seong-Eui,Lee. Kyoo-Yeol,Choi. Do-Il,Chung. Hae-Young,Hur. Cheol-Goo
간행물명
Genomics & informatics
권/호정보
2006년|4권 2호|pp.87-93 (7 pages)
발행정보
한국유전체학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

With the rapid development of MS technologiesy, 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). Abbreviations: fBIND, fingerprinting using binomial distribution; GO, Gene Ontology; MS, Mass Spectrometry; PMF, peptide mass fingerprinting; nr, nonredundant; SGD, Saccharomyces Genome Database