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BMCBI
2007
164views more  BMCBI 2007»
14 years 9 months ago
Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...
BMCBI
2010
150views more  BMCBI 2010»
14 years 9 months ago
Systematic calibration of a cell signaling network model
Background: Mathematical modeling is being applied to increasingly complex biological systems and datasets; however, the process of analyzing and calibrating against experimental ...
Kyoung Ae Kim, Sabrina L. Spencer, John G. Albeck,...
IJKDB
2010
141views more  IJKDB 2010»
14 years 6 months ago
Mining Frequent Boolean Expressions: Application to Gene Expression and Regulatory Modeling
Regulatory network analysis and other bioinformatics tasks require the ability to induce and represent arbitrary boolean expressions from data sources. We introduce a novel framew...
Mohammed Javeed Zaki, Naren Ramakrishnan, Lizhuang...
CORR
2011
Springer
149views Education» more  CORR 2011»
14 years 4 months ago
General Iteration graphs and Boolean automata circuits
This article is set in the eld of regulation networks modeled by discrete dynamical systems. It focuses on Boolean automata networks. In such networks, there are many ways to upd...
Mathilde Noual
ALMOB
2006
80views more  ALMOB 2006»
14 years 9 months ago
Pattern statistics on Markov chains and sensitivity to parameter estimation
Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter mu...
Grégory Nuel