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BMCBI
2010
97views more  BMCBI 2010»
12 years 12 months ago
A semi-parametric Bayesian model for unsupervised differential co-expression analysis
Background: Differential co-expression analysis is an emerging strategy for characterizing disease related dysregulation of gene expression regulatory networks. Given pre-defined ...
Johannes M. Freudenberg, Siva Sivaganesan, Michael...
BMCBI
2007
149views more  BMCBI 2007»
13 years 5 months ago
A unified framework for finding differentially expressed genes from microarray experiments
Background: This paper presents a unified framework for finding differentially expressed genes (DEGs) from the microarray data. The proposed framework has three interrelated modul...
Jahangheer S. Shaik, Mohammed Yeasin
FUIN
2011
358views Cryptology» more  FUIN 2011»
12 years 8 months ago
Unsupervised and Supervised Learning Approaches Together for Microarray Analysis
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
Indrajit Saha, Ujjwal Maulik, Sanghamitra Bandyopa...
BMCBI
2008
158views more  BMCBI 2008»
13 years 5 months ago
Analyzing M-CSF dependent monocyte/macrophage differentiation: Expression modes and meta-modes derived from an independent compo
Background: The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and ...
Dominik Lutter, Peter Ugocsai, Margot Grandl, Evel...
BMCBI
2010
161views more  BMCBI 2010»
13 years 5 months ago
GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms
Background: An important objective of DNA microarray-based gene expression experimentation is determining interrelationships that exist between differentially expressed genes and ...
Saurin D. Jani, Gary L. Argraves, Jeremy L. Barth,...