Using the information embedded in the testing sample to break the limits caused by the small sample size in microarray-based classification

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Zhu, Manli ^a   Martinez, Aleix M ^a  

^a Ohio State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ALGORITHM; CLASSIFICATION RESULTS; MOLECULAR VARIATION; NUMBER OF SAMPLES; SMALL SAMPLE SIZE; STATISTICAL INFORMATION; STATISTICAL TECHNIQUES; TUMOR CLASSIFICATION;

ALGORITHMS; GENES; INFORMATION USE; TUMORS;

DATA MINING;

ACUTE LYMPHOBLASTIC LEUKEMIA; ACUTE MYELOBLASTIC LEUKEMIA; ARTICLE; B CELL LYMPHOMA; BREAST CANCER; CLASSIFICATION ALGORITHM; COLON CANCER; DNA MICROARRAY; GENETIC ALGORITHM; GENETIC DATABASE; INFORMATION PROCESSING; INFORMATION RETRIEVAL; LARGE CELL LYMPHOMA; PROSTATE CANCER; SAMPLE SIZE; STATISTICAL ANALYSIS; TUMOR CLASSIFICATION; ALGORITHM; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; HUMAN; METHODOLOGY; NEOPLASM;

ALGORITHMS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 46949104413     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-280     Document Type: Article

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