Uncovering Gene Regulatory Networks from Time-Series Microarray Data with Variational Bayesian Structural Expectation Maximization

We investigate in this paper reverse engineering of gene regulatory networks from time-series microarray data. We apply dynamic Bayesian networks (DBNs) for modeling cell cycle regulations. In developing a network inference algorithm, we focus on soft solutions that can provide a posteriori probabil...

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Detalles Bibliográficos
Autores principales: Luna, Isabel Tienda, Huang, Yufei, Yin, Yufang, Padillo, Diego P Ruiz, Perez, M Carmen Carrion
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2007
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171349/
https://www.ncbi.nlm.nih.gov/pubmed/18309364
http://dx.doi.org/10.1155/2007/71312

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171349/
https://www.ncbi.nlm.nih.gov/pubmed/18309364
http://dx.doi.org/10.1155/2007/71312

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