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» Background knowledge for ontology construction
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IJAR
2010
130views more  IJAR 2010»
14 years 8 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
BIOCOMP
2008
14 years 11 months ago
Reverse Engineering Module Networks by PSO-RNN Hybrid Modeling
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...
BMCBI
2008
114views more  BMCBI 2008»
14 years 9 months ago
Partial mixture model for tight clustering of gene expression time-course
Background: Tight clustering arose recently from a desire to obtain tighter and potentially more informative clusters in gene expression studies. Scattered genes with relatively l...
Yinyin Yuan, Chang-Tsun Li, Roland Wilson
BMCBI
2008
122views more  BMCBI 2008»
14 years 9 months ago
Reconstructing networks of pathways via significance analysis of their intersections
Background: Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statist...
Mirko Francesconi, Daniel Remondini, Nicola Nerett...
BMCBI
2007
177views more  BMCBI 2007»
14 years 9 months ago
The BioPrompt-box: an ontology-based clustering tool for searching in biological databases
Background: High-throughput molecular biology provides new data at an incredible rate, so that the increase in the size of biological databanks is enormous and very rapid. This sc...
Claudio Corsi, Paolo Ferragina, Roberto Marangoni