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PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 6 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
BMCBI
2007
143views more  BMCBI 2007»
13 years 7 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
BMCBI
2008
86views more  BMCBI 2008»
13 years 7 months ago
Piecewise multivariate modelling of sequential metabolic profiling data
Background: Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the...
Mattias Rantalainen, Olivier Cloarec, Timothy M. D...
ALMOB
2006
80views more  ALMOB 2006»
13 years 7 months ago
Pattern statistics on Markov chains and sensitivity to parameter estimation
Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter mu...
Grégory Nuel
BMCBI
2006
116views more  BMCBI 2006»
13 years 7 months ago
Optimized mixed Markov models for motif identification
Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...