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BMCBI
2010
153views more  BMCBI 2010»
15 years 6 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
2010
153views more  BMCBI 2010»
15 years 6 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
BMCBI
2010
143views more  BMCBI 2010»
15 years 6 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
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BMCBI
2004
117views more  BMCBI 2004»
15 years 6 months ago
Cancer characterization and feature set extraction by discriminative margin clustering
Background: A central challenge in the molecular diagnosis and treatment of cancer is to define a set of molecular features that, taken together, distinguish a given cancer, or ty...
Kamesh Munagala, Robert Tibshirani, Patrick O. Bro...
RECOMB
2002
Springer
16 years 6 months ago
A bayesian approach to transcript estimation from gene array data: the BEAM technique
We present a new statistically optimal approach to estimate transcript levels and ratios from one or more gene array experiments. The Bayesian Estimation of Array Measurements (BE...
Ron O. Dror, Jonathan G. Murnick, Nicola A. Rinald...