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ICPR
2006
IEEE
14 years 6 months ago
Exploiting the Geometry of Gene Expression Patterns for Unsupervised Learning
Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may ...
Rave Harpaz, Robert M. Haralick
CVPR
2005
IEEE
14 years 7 months ago
Joint Nonparametric Alignment for Analyzing Spatial Gene Expression Patterns in Drosophila Imaginal Discs
To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing i...
Parvez Ahammad, Cyrus L. Harmon, Ann Hammonds, Sha...
RECOMB
2007
Springer
14 years 5 months ago
Learning Gene Regulatory Networks via Globally Regularized Risk Minimization
Learning the structure of a gene regulatory network from time-series gene expression data is a significant challenge. Most approaches proposed in the literature to date attempt to ...
Yuhong Guo, Dale Schuurmans
BMCBI
2006
183views more  BMCBI 2006»
13 years 5 months ago
Mining gene expression data by interpreting principal components
Background: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many insta...
Joseph C. Roden, Brandon W. King, Diane Trout, Ali...
BMCBI
2010
143views more  BMCBI 2010»
13 years 5 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