Application of machine learning to proteomics data: Classification and biomarker identification in postgenomics biology

OMICS A Journal of Integrative Biology

Volumn 17, Issue 12, 2013, Pages 595-610

  Swan, Anna Louise ^a   Mobasheri, Ali ^a,b,d,e,f   Allaway, David ^c   Liddell, Susan ^a   Bacardit, Jaume ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^c WALTHAM CENTRE FOR PET NUTRITION   (United Kingdom)

^d NOTTINGHAM UNIVERSITY HOSPITALS NHS TRUST   (United Kingdom)

^e KING ABDULAZIZ UNIVERSITY   (Saudi Arabia)

^f UNIVERSITY OF BRADFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; CLASSIFICATION ALGORITHM; COMPUTER PROGRAM; DATA ANALYSIS; DATA MINING; DECISION TREE; DIAGNOSTIC TEST; FEATURE SELECTION METHOD; HUMAN; MACHINE LEARNING; PRIORITY JOURNAL; PROGNOSIS; PROTEIN ANALYSIS; PROTEOMICS; RANDOM FOREST; REVIEW; RULE BASED LEARNER; SEARCH ENGINE; SUPPORT VECTOR MACHINE; TANDEM MASS SPECTROMETRY; VALIDATION PROCESS;

ARTIFICIAL INTELLIGENCE; BIOLOGICAL MARKERS; HUMANS; MASS SPECTROMETRY; PROTEOME; PROTEOMICS; TANDEM MASS SPECTROMETRY;

EID: 84888212150     PISSN: 15362310     EISSN: 15578100     Source Type: Journal    
DOI: 10.1089/omi.2013.0017     Document Type: Review

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