Normalization Using Weighted Negative Second Order Exponential Error Functions (NeONORM) Provides Robustness Against Asymmetries in Comparative Transcriptome Profiles and Avoids False Calls

Genomics, Proteomics and Bioinformatics

Volumn 4, Issue 2, 2006, Pages 90-109

  Noth, Sebastian ^a   Brysbaert, Guillaume ^a   Benecke, Arndt ^a  

^a INSTITUT DES HAUTES ÉTUDES SCIENTIFIQUES   (France)

Author keywords

asymmetry; microarray; normalization; robustness; statistical analysis

Indexed keywords

TRANSCRIPTOME;

ALGORITHM; ARTICLE; BIOINFORMATICS; COMPARATIVE STUDY; CONTROLLED STUDY; DATA ANALYSIS; GENE CONTROL; GENE EXPRESSION; HUMAN; HUMAN CELL; HYPOTHESIS; MATHEMATICAL ANALYSIS; MICROARRAY ANALYSIS; NEONORM METHOD; STATISTICAL ANALYSIS; VALIDATION STUDY;

ALGORITHMS; CELL LINE, TUMOR; DATA INTERPRETATION, STATISTICAL; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; MODELS, GENETIC; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED;

EID: 33747330684     PISSN: 16720229     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1672-0229(06)60021-1     Document Type: Article

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