Probability-based pattern recognition and statistical framework for randomization: modeling tandem mass spectrum/peptide sequence false match frequencies | Zendy

Jian Feng | Zendy; Daniel Q. Naiman | Zendy; Bret Cooper | Zendy

Open Access

Probability-based pattern recognition and statistical framework for randomization: modeling tandem mass spectrum/peptide sequence false match frequencies

Author(s) -

Jian Feng,

Daniel Q. Naiman,

Bret Cooper

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm267

Subject(s) - computer science , sequence database , software , sequence (biology) , database search engine , pattern recognition (psychology) , identification (biology) , data mining , false discovery rate , decoy , artificial intelligence , information retrieval , search engine , biology , botany , receptor , genetics , biochemistry , gene , programming language

In proteomics, reverse database searching is used to control the false match frequency for tandem mass spectrum/peptide sequence matches, but reversal creates sequences devoid of patterns that usually challenge database-search software.

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