Improved Algorithms for the Identification of Yeast Proteins and Significant Transcription Factor and Motif Analysis.
- Author:
Seung Won LEE
1
;
Seong Eui HONG
;
Kyoo Yeol LEE
;
Do Il CHOI
;
Hae Young CHUNG
;
Cheol Goo HUR
Author Information
1. Korea Research Institute of Bioscience and Biotechnology, Korea. hurlee@kribb.re.kr
- Publication Type:Original Article
- Keywords:
peptide mass fingerprinting;
molecular weight search;
binomial distribution;
hypergeometric distribution
- MeSH:
Binomial Distribution;
Fungal Proteins*;
Gene Ontology;
Peptide Mapping;
Transcription Factors*;
Wool;
Yeasts*
- From:Genomics & Informatics
2006;4(2):87-93
- CountryRepublic of Korea
- Language:English
-
Abstract:
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).
