A machine learning approach to predicting peptide fragmentation spectra

Proceedings of the Pacific Symposium on Biocomputing 2006, PSB 2006

Volumn , Issue , 2006, Pages 219-230

  Arnold, Randy J ^a   Jayasankar, Narmada ^b   Aggarwal, Divya ^b   Tang, Haixu ^a,b   Radivojac, Predrag ^b  

^a INDIANA UNIVERSITY   (United States)

^b INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BOND CLEAVAGES; DATA-DRIVEN APPROACH; EXPERIMENTAL SPECTRA; MACHINE LEARNING APPROACHES; NEW APPROACHES; NON-UNIFORM; PEPTIDE DATABASE SEARCH; PEPTIDE FRAGMENTATION; PEPTIDE IDENTIFICATION; POSTERIOR PROBABILITY; PRECURSOR IONS; PROTEOMICS; SENSITIVITY AND SPECIFICITY; SEQUEST; TANDEM MASS;

IONS; MASS SPECTROMETRY; MOLECULAR BIOLOGY; SEARCH ENGINES;

PEPTIDES;

AMINO ACID; PEPTIDE;

ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; EVALUATION; PROTEIN DATABASE; STATISTICS; TANDEM MASS SPECTROMETRY;

AMINO ACIDS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; MOLECULAR STRUCTURE; PEPTIDES; TANDEM MASS SPECTROMETRY;

EID: 36348959863     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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