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» Geometry of gene expression dynamics
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BMCBI
2010
214views more  BMCBI 2010»
15 years 2 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
BMCBI
2007
133views more  BMCBI 2007»
15 years 1 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
ECCB
2003
IEEE
15 years 7 months ago
Gene networks inference using dynamic Bayesian networks
This article deals with the identification of gene regulatory networks from experimental data using a statistical machine learning approach. A stochastic model of gene interactio...
Bruno-Edouard Perrin, Liva Ralaivola, Aurél...
BMCBI
2010
160views more  BMCBI 2010»
15 years 2 months ago
Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53
Background: The availability of various "omics" datasets creates a prospect of performing the study of genomewide genetic regulatory networks. However, one of the major ...
Junbai Wang, Tianhai Tian
130
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BMCBI
2007
148views more  BMCBI 2007»
15 years 1 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...