A novel strategy for molecular signature discovery based on independent component analysis

International Journal of Data Mining and Bioinformatics

Volumn 9, Issue 3, 2014, Pages 277-304

  Pham, Hang Phuong ^a,b   Dérian, Nicolas ^a,b   Chaara, Wahiba ^a,b   Bellier, Bertrand ^a,b,c   Klatzmann, David ^a,b,c   Six, Adrien ^a,b  

^a SORBONNE UNIVERSITÉ   (France)

^b CNRS   (France)

^c INSERM   (France)

Author keywords

Bioinformatics; Data mining; Gene expression; Gene set enrichment analysis; GSEA; ICA; Independent component analysis; Microarray data analysis; Molecular signature; Regulatory T cell; Signature discovery; Statistical modelling; Tlymphocyte; Transcriptome; Treg

Indexed keywords

ADENOVIRUS VACCINE;

ADENOVIRUS; ALGORITHM; ANIMAL; ARTICLE; BIOLOGY; C57BL MOUSE; COMPUTER PROGRAM; CYTOLOGY; DATA MINING; DNA MICROARRAY; FEMALE; METABOLISM; METHODOLOGY; MOUSE; REGULATORY T LYMPHOCYTE; SPLEEN;

ADENOVIRIDAE; ADENOVIRUS VACCINES; ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; DATA MINING; FEMALE; MICE; MICE, INBRED C57BL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SOFTWARE; SPLEEN; T-LYMPHOCYTES, REGULATORY;

EID: 84897387168     PISSN: 17485673     EISSN: 17485681     Source Type: Journal    
DOI: 10.1504/IJDMB.2014.060052     Document Type: Article

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