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BMCBI
2007
146views more  BMCBI 2007»
14 years 9 months ago
Bayesian hierarchical model for transcriptional module discovery by jointly modeling gene expression and ChIP-chip data
Background: Transcriptional modules (TM) consist of groups of co-regulated genes and transcription factors (TF) regulating their expression. Two high-throughput (HT) experimental ...
Xiangdong Liu, Walter J. Jessen, Siva Sivaganesan,...
AAAI
2010
14 years 11 months ago
Searching Without a Heuristic: Efficient Use of Abstraction
g Without a Heuristic: Efficient Use of Abstraction Bradford Larsen, Ethan Burns, Wheeler Ruml Department of Computer Science University of New Hampshire Durham, NH 03824 USA blars...
Bradford John Larsen, Ethan Burns, Wheeler Ruml, R...
BMCBI
2006
85views more  BMCBI 2006»
14 years 9 months ago
Quality control for terms and definitions in ontologies and taxonomies
Background: Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the G...
Jacob Köhler, Katherine Munn, Alexander R&uum...
BMCBI
2006
126views more  BMCBI 2006»
14 years 9 months ago
A joint model of regulatory and metabolic networks
Background: Gene regulation and metabolic reactions are two primary activities of life. Although many works have been dedicated to study each system, the coupling between them is ...
Chen-Hsiang Yeang, Martin Vingron
PAMI
2008
161views more  PAMI 2008»
14 years 9 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...