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ALMOB
2007
111views more  ALMOB 2007»
14 years 9 months ago
Transcriptional regulatory network discovery via multiple method integration: application to e. coli K12
Motivation: Transcriptional regulatory network (TRN) discovery from one method (e.g. microarray analysis, gene ontology, phylogenic similarity) does not seem feasible due to lack ...
Jingjun Sun, Kagan Tuncay, Alaa Abi Haidar, Lisa E...
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, ...
ISMB
2000
14 years 11 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
119
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BMCBI
2007
106views more  BMCBI 2007»
14 years 9 months ago
Modeling SAGE tag formation and its effects on data interpretation within a Bayesian framework
Background: Serial Analysis of Gene Expression (SAGE) is a high-throughput method for inferring mRNA expression levels from the experimentally generated sequence based tags. Stand...
Michael A. Gilchrist, Hong Qin, Russell L. Zaretzk...
92
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BMCBI
2010
165views more  BMCBI 2010»
14 years 9 months ago
Filtering, FDR and power
Background: In high-dimensional data analysis such as differential gene expression analysis, people often use filtering methods like fold-change or variance filters in an attempt ...
Maarten van Iterson, Judith M. Boer, Renée ...