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» A new approach to analyzing gene expression time series data
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BMCBI
2007
144views more  BMCBI 2007»
14 years 9 months ago
Robust regression for periodicity detection in non-uniformly sampled time-course gene expression data
Background: In practice many biological time series measurements, including gene microarrays, are conducted at time points that seem to be interesting in the biologist's opin...
Miika Ahdesmäki, Harri Lähdesmäki, ...
BMCBI
2007
173views more  BMCBI 2007»
14 years 9 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
BMCBI
2008
158views more  BMCBI 2008»
14 years 9 months ago
Analyzing M-CSF dependent monocyte/macrophage differentiation: Expression modes and meta-modes derived from an independent compo
Background: The analysis of high-throughput gene expression data sets derived from microarray experiments still is a field of extensive investigation. Although new approaches and ...
Dominik Lutter, Peter Ugocsai, Margot Grandl, Evel...
BMCBI
2006
155views more  BMCBI 2006»
14 years 9 months ago
Analysis of promoter regions of co-expressed genes identified by microarray analysis
Background: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biol...
Srinivas Veerla, Mattias Höglund
BMCBI
2006
239views more  BMCBI 2006»
14 years 9 months ago
Applying dynamic Bayesian networks to perturbed gene expression data
Background: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics,...
Norbert Dojer, Anna Gambin, Andrzej Mizera, Bartek...