In silico identification software (ISIS): A machine learning approach to tandem mass spectral identification of lipids

Bioinformatics

Volumn 28, Issue 13, 2012, Pages 1705-1713

  Kangas, Lars J ^a   Metz, Thomas O ^a   Isaac, Giorgis ^a   Schrom, Brian T ^a   Ginovska Pangovska, Bojana ^a   Wang, Luning ^b   Tan, Li ^b   Lewis, Robert R ^b   Miller, John H ^b  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^b WASHINGTON STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LIPID;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; CHEMISTRY; COMPUTER PROGRAM; COMPUTER SIMULATION; METABOLOMICS; METHODOLOGY; SENSITIVITY AND SPECIFICITY; TANDEM MASS SPECTROMETRY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; LIPIDS; METABOLOMICS; SENSITIVITY AND SPECIFICITY; SOFTWARE; TANDEM MASS SPECTROMETRY;

EID: 84864008587     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/bts194     Document Type: Article

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