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» On Timed Models of Gene Networks
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BMCBI
2008
166views more  BMCBI 2008»
13 years 8 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf
EVOW
2007
Springer
14 years 2 months ago
Modeling Genetic Networks: Comparison of Static and Dynamic Models
Biomedical research has been revolutionized by high-throughput techniques and the enormous amount of biological data they are able to generate. The interest shown over network mode...
Cristina Rubio-Escudero, Oscar Harari, Oscar Cord&...
IDA
2002
Springer
13 years 7 months ago
A framework for modelling virus gene expression data
Short, high-dimensional, Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would b...
Paul Kellam, Xiaohui Liu, Nigel J. Martin, Christi...
IJKDB
2010
141views more  IJKDB 2010»
13 years 5 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...
CEC
2009
IEEE
13 years 12 months ago
A model for intrinsic artificial development featuring structural feedback and emergent growth
Abstract--A model for intrinsic artificial development is introduced in this paper. The proposed model features a novel mechanism where growth emerges, rather than being triggered ...
Martin Trefzer, Tüze Kuyucu, Julian Francis M...