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BMCBI
2005
140views more  BMCBI 2005»
15 years 6 months ago
Dissecting systems-wide data using mixture models: application to identify affected cellular processes
Background: Functional analysis of data from genome-scale experiments, such as microarrays, requires an extensive selection of differentially expressed genes. Under many condition...
J. Peter Svensson, Renée X. de Menezes, Ing...
ACIIDS
2010
IEEE
170views Database» more  ACIIDS 2010»
15 years 4 months ago
On the Effectiveness of Gene Selection for Microarray Classification Methods
Microarray data usually contains a high level of noisy gene data, the noisy gene data include incorrect, noise and irrelevant genes. Before Microarray data classification takes pla...
Zhongwei Zhang, Jiuyong Li, Hong Hu, Hong Zhou
BMCBI
2004
134views more  BMCBI 2004»
15 years 6 months ago
Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)
Background: An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature ...
Ricardo Z. N. Vêncio, Helena Brentani, Diogo...
GFKL
2005
Springer
141views Data Mining» more  GFKL 2005»
15 years 12 months ago
On External Indices for Mixtures: Validating Mixtures of Genes
Mixture models represent results of gene expression cluster analysis in a more natural way than ’hard’ partitions. This is also true for the representation of gene labels, such...
Ivan G. Costa, Alexander Schliep
KDD
2004
ACM
145views Data Mining» more  KDD 2004»
16 years 6 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...