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BMCBI
2007
151views more  BMCBI 2007»
8 years 9 months ago
A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microar
Background: The incorporation of prior biological knowledge in the analysis of microarray data has become important in the reconstruction of transcription regulatory networks in a...
Peter Larsen, Eyad Almasri, Guanrao Chen, Yang Dai
BMCBI
2007
152views more  BMCBI 2007»
8 years 9 months ago
Difference-based clustering of short time-course microarray data with replicates
Background: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain know...
Jihoon Kim, Ju Han Kim
DILS
2008
Springer
8 years 11 months ago
Semi Supervised Spectral Clustering for Regulatory Module Discovery
We propose a novel semi-supervised clustering method for the task of gene regulatory module discovery. The technique uses data on dna binding as prior knowledge to guide the proces...
Alok Mishra, Duncan Gillies
BMCBI
2010
172views more  BMCBI 2010»
8 years 9 months ago
Inferring gene regression networks with model trees
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
Isabel A. Nepomuceno-Chamorro, Jesús S. Agu...
BIBE
2006
IEEE
160views Bioinformatics» more  BIBE 2006»
9 years 3 months ago
Methods for Random Modularization of Biological Networks
— Biological networks are formalized summaries of our knowledge about interactions among biological system components, like genes, proteins, or metabolites. From their global top...
Zachary M. Saul, Vladimir Filkov
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