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» Geometry of gene expression dynamics
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BMCBI
2010
214views more  BMCBI 2010»
13 years 7 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»
13 years 7 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
14 years 25 days 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»
13 years 7 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
BMCBI
2007
148views more  BMCBI 2007»
13 years 7 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...