Kernel density weighted loess normalization improves the performance of detection within asymmetrical data

BMC Bioinformatics

Volumn 12, Issue , 2011, Pages

  Hsieh, Wen Ping ^a   Chu, Tzu Ming ^b   Lin, Yu Min ^b   Wolfinger, Russell D ^b  

^a NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^b SAS INSTITUTE INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPRESSION RATES; GENE EXPRESSION DATA; KERNEL DENSITY; KERNEL DENSITY ESTIMATION; NORMALIZATION ALGORITHMS; REGULATED GENES; SIMILAR DEGREE; SIMULATION DATA;

GENE EXPRESSION; GOLD;

EXPERIMENTS;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; COMPUTER PROGRAM; DNA MICROARRAY; GENE EXPRESSION PROFILING; HUMAN; METHODOLOGY; RECEIVER OPERATING CHARACTERISTIC; REGRESSION ANALYSIS;

ALGORITHMS; CLUSTER ANALYSIS; GENE EXPRESSION PROFILING; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REGRESSION ANALYSIS; ROC CURVE; SOFTWARE;

EID: 79957639306     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-222     Document Type: Article

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