Determination of Tumour Marker Genes from Gene Expression Data

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Journal titleAcoustics, Speech, and Signal Processing Newsletter, IEEE
Subjectmicroarray; gene analysis; gene selections; tumour classification; marker genes; tumour diagnostics; feature analysis; feature selection; analyse génétique; choix des gènes; classification des tumeurs; gènes marqueurs; diagnostic des tumeurs; analyse des caractéristiques; choix des caractéristiques
AbstractCancer classification has traditionally been based on the morphological study of tumours. However, tumours with similar histological appearances can exhibit different responses to therapy, indicating differences in tumour characteristics on the molecular level. Thus, development of a novel, reliable and precise method for classification of tumours is essential for more successful diagnosis and treatment. The high-throughput gene expression data obtained using microarray technology are currently being investigated for diagnostic applications. However, these large datasets introduce a range of challenges, making data analysis a major part of every experiment for any application, including cancer classification and diagnosis. One of the major concerns in the application of microarrays to tumour diagnostics is the fact that the expression levels of many genes are not measurably affected by carcinogenic changes in the cells. Thus, a crucial step in the application of microarrays to cancer diagnostics is the selection of diagnostic marker genes from the gene expression profiles. These molecular markers give valuable additional information for tumour diagnosis, prognosis and therapy development.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48052
NPARC number8913239
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Record identifiere2e114c5-bb7e-4cb7-86a5-b93b8f55c2a0
Record created2009-04-22
Record modified2016-05-09
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