Literature DB >> 23573658

Diagnostic signatures from microarrays: a bioinformatics concept for personalized medicine.

Rainer Spang1.   

Abstract

Microarrays can be used as diagnostic clinical tools, providing a global overview of gene transcription in diseased tissues. Expression profiles can be easily obtained in a single assay and provide exhaustive information about molecular events that are often directly linked to the cause of a disease. However, the high complexity of the data are challenging. This article reviews recent efforts in bioinformatics and statistics to overcome this problem and make feasible the clinical analysis of gene expression profiles.

Mesh:

Year:  2004        PMID: 23573658

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  5 in total

1.  Quantitative PCR on 5 genes reliably identifies CTCL patients with 5% to 99% circulating tumor cells with 90% accuracy.

Authors:  Michael Nebozhyn; Andrey Loboda; Laszlo Kari; Alain H Rook; Eric C Vonderheid; Stuart Lessin; Carole Berger; Richard Edelson; Calen Nichols; Malik Yousef; Lalitha Gudipati; Meiling Shang; Michael K Showe; Louise C Showe
Journal:  Blood       Date:  2006-01-10       Impact factor: 22.113

2.  A new locally weighted K-means for cancer-aided microarray data analysis.

Authors:  Natthakan Iam-On; Tossapon Boongoen
Journal:  J Med Syst       Date:  2012-10-28       Impact factor: 4.460

3.  Network based consensus gene signatures for biomarker discovery in breast cancer.

Authors:  Holger Fröhlich
Journal:  PLoS One       Date:  2011-10-25       Impact factor: 3.240

4.  Constrained mixture estimation for analysis and robust classification of clinical time series.

Authors:  Ivan G Costa; Alexander Schönhuth; Christoph Hafemeister; Alexander Schliep
Journal:  Bioinformatics       Date:  2009-06-15       Impact factor: 6.937

5.  Clustering cancer gene expression data: a comparative study.

Authors:  Marcilio C P de Souto; Ivan G Costa; Daniel S A de Araujo; Teresa B Ludermir; Alexander Schliep
Journal:  BMC Bioinformatics       Date:  2008-11-27       Impact factor: 3.169

  5 in total

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