Analysis of array CGH data: from signal ratio to gain and loss of DNA regions | Zendy

Philippe Hupé | Zendy; Nicolas Stransky | Zendy; Jean Paul Thiery | Zendy; François Radvanyi | Zendy; Emmanuel Barillot | Zendy

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Analysis of array CGH data: from signal ratio to gain and loss of DNA regions

Author(s) -

Philippe Hupé,

Nicolas Stransky,

Jean Paul Thiery,

François Radvanyi,

Emmanuel Barillot

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bth418

Subject(s) - signal (programming language) , computer science , dna , algorithm , computational biology , genetics , biology , programming language

Genomic DNA regions are frequently lost or gained during tumor progression. Array Comparative Genomic Hybridization (array CGH) technology makes it possible to assess these changes in DNA in cancers, by comparison with a normal reference. The identification of systematically deleted or amplified genomic regions in a set of tumors enables biologists to identify genes involved in cancer progression because tumor suppressor genes are thought to be located in lost genomic regions and oncogenes, in gained regions. Array CGH profiles should also improve the classification of tumors. The achievement of these goals requires a methodology for detecting the breakpoints delimiting altered regions in genomic patterns and assigning a status (normal, gained or lost) to each chromosomal region.

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