Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Wang, Bing ^a,b   Valentine, Steve ^c   Plasencia, Manolo ^c   Raghuraman, Sriram ^d   Zhang, Xiang ^b  

^a ANHUI UNIVERSITY OF TECHNOLOGY   (China)

^b UNIVERSITY OF LOUISVILLE   (United States)

^c INDIANA UNIVERSITY   (United States)

^d Predictive Physiology and Medicine   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

10-FOLD CROSS-VALIDATION; AMINO ACID SEQUENCE; EFFECTIVENESS AND EFFICIENCIES; EXPERIMENT CONDITION; ION MOBILITY SPECTROMETRY; ION MOBILITY-MASS SPECTROMETRY; PREDICTION ACCURACY; PROTEIN IDENTIFICATION;

AMINO ACIDS; FORECASTING; ION MOBILITY SPECTROMETERS; IONS; MASS SPECTROMETRY; MATHEMATICAL MODELS; MOLECULAR BIOLOGY; NEURAL NETWORKS; REGRESSION ANALYSIS; SEARCH ENGINES;

PEPTIDES;

ION; PEPTIDE; PROTEIN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CHEMISTRY; MASS SPECTROMETRY; METHODOLOGY; PROTEOMICS;

IONS; MASS SPECTROMETRY; NEURAL NETWORKS (COMPUTER); PEPTIDES; PROTEINS; PROTEOMICS;

EID: 77950664005     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-182     Document Type: Article

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