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» Can we Find Molecular Signatures from Gene Expression Data
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ITA
2006
167views Communications» more  ITA 2006»
13 years 8 months ago
Characterization of lung tumor subtypes through gene expression cluster validity assessment
The problem of assessing the reliability of clusters patients identified by clustering algorithms is crucial to estimate the significance of subclasses of diseases detectable at b...
Giorgio Valentini, Francesca Ruffino
BMCBI
2004
180views more  BMCBI 2004»
13 years 8 months ago
Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovaria
Background: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identi...
Virginie M. Aris, Michael J. Cody, Jeff Cheng, Jam...
BMCBI
2007
156views more  BMCBI 2007»
13 years 8 months ago
Large-scale clustering of CAGE tag expression data
Background: Recent analyses have suggested that many genes possess multiple transcription start sites (TSSs) that are differentially utilized in different tissues and cell lines. ...
Kazuro Shimokawa, Yuko Okamura-Oho, Takio Kurita, ...
BMCBI
2010
96views more  BMCBI 2010»
13 years 8 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
ICANN
2009
Springer
13 years 6 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...