Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria

PLoS Computational Biology

Volumn 9, Issue 4, 2013, Pages

  Rousu, Juho ^a,b   Agranoff, Daniel D ^c   Sodeinde, Olugbemiro ^b,d   Shawe Taylor, John ^e   Fernandez Reyes, Delmiro ^b,d,e  

^a AALTO UNIVERSITY   (Finland)

^b UNIVERSITY OF IBADAN   (Nigeria)

^c WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

^d NATIONAL INSTITUTE FOR MEDICAL RESEARCH   (United Kingdom)

^e UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION METHODS; DISEASES; MOLECULAR BIOLOGY;

'CURRENT; 'OMICS'; BIO-MARKER DISCOVERY; CLASS PREDICTION; CLINICAL BIOMARKERS; CLINICAL PARAMETERS; CLINICAL SYNDROMES; COMPUTATIONAL APPROACH; SPARSE CANONICAL CORRELATION ANALYSIS; UNIVARIATE;

BIOMARKERS;

BIOLOGICAL MARKER;

ACCURACY; ALGORITHM; ARTICLE; BLOOD ANALYSIS; COMPLEX FORMATION; CORRELATION ANALYSIS; DATA ANALYSIS; DECISION SUPPORT SYSTEM; GENETIC ASSOCIATION; HUMAN; MALARIA; PHENOTYPE; PREDICTION; PROTEOMICS; TUBERCULOSIS; VALIDATION PROCESS;

EID: 84876931551     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003018     Document Type: Article

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