Analyzing array data using supervised methods.
Pharmacogenomics is the application of genomic technologies to drug discovery and development, as well as for the elucidation of the mechanisms of drug action on cells and organisms. DNA microarrays measure genome-wide gene expression patterns and are an important tool for pharmacogenomic applications, such as the identification of molecular targets for drugs, toxicological studies and molecular diagnostics. Genome-wide investigations generate vast amounts of data and there is a need for computational methods to manage and analyze this information. Recently, several supervised methods, in which other information is utilized together with gene expression data, have been used to characterize genes and samples. The choice of analysis methods will influence the results and their interpretation, therefore it is important to be familiar with each method, its scope and limitations. Here, methods with special reference to applications for pharmacogenomics are reviewed.
Ringnér
Markus
M
Cancer Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Building 50, Room 5142,50 South Drive MSC 8000, Bethesda, MD 20892, USA. mringner@nhgri.nih.gov.
Peterson
Carsten
C
Khan
Javed
J
D001185:Artificial Intelligence; D003627:Data Interpretation, Statistical; D016571:Neural Networks, Computer; D020411:Oligonucleotide Array Sequence Analysis / Q000706:statistics & numerical data*; D011506:Proteins / Q000145:classification / Q000235:genetics
D011506:Proteins