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  Detecting common gene expression patterns in multiple cancer outcome entities

Yang, X., Bentink, S., & Spang, R. (2005). Detecting common gene expression patterns in multiple cancer outcome entities. Biomedical Microdevices, 7(3), 247-251. doi:10.1007/s10544-005-3032-7.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-8598-4 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-8599-2
Genre: Journal Article
Alternative Title : Biomed Microdevices

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x434q3324h71h467.pdf (Any fulltext), 523KB
 
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 Creators:
Yang, Xinan1, Author
Bentink, Stefan1, Author
Spang, Rainer2, Author              
Affiliations:
1Max Planck Society, ou_persistent13              
2Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433547              

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Free keywords: molecular cancer mechanisms meta-analysis computational diagnostics microarrays bioinformatics
 Abstract: Most oncological microarray studies focus on molecular distinctions in different cancer entities. Recently, researchers started using microarrays for investigating molecular commonalities of multiple cancer types. This poses novel bioinformatics challenges. In this paper we describe a method that detects common molecular mechanisms in different cancer entities. The method extends previously described concepts by introducing Meta-Analysis Pattern Matches. In an analysis of four prognostic cancer studies, involving breast cancer, leukemia, and mesothelioma, we are able to identify 42 genes that show consistent up- or down-regulation in patients with a poor disease outcome. These genes complement the set of previously published candidates for universal prognostic markers in cancer.

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Language(s): eng - English
 Dates: 2005-09-01
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 268537
DOI: 10.1007/s10544-005-3032-7
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Title: Biomedical Microdevices
  Alternative Title : Biomed Microdevices
Source Genre: Journal
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Publ. Info: -
Pages: - Volume / Issue: 7 (3) Sequence Number: - Start / End Page: 247 - 251 Identifier: ISSN: 1387-2176