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BMCBI
2008
160views more  BMCBI 2008»
13 years 8 months ago
Predicting cancer involvement of genes from heterogeneous data
Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characte...
Ramon Aragues, Chris Sander, Baldo Oliva
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
14 years 8 months ago
Mining coherent gene clusters from gene-sample-time microarray data
Extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. In this paper, we explore a novel type of genesa...
Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tan...
ITA
2006
167views Communications» more  ITA 2006»
13 years 7 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
2010
153views more  BMCBI 2010»
13 years 8 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
BMCBI
2007
147views more  BMCBI 2007»
13 years 8 months ago
Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
Scott D. Zuyderduyn