Predicting transcriptional regulatory interactions with artificial neural networks applied to E. coli multidrug resistance efflux pumps

BACKGROUND: Little is known about bacterial transcriptional regulatory networks (TRNs). In Escherichia coli, which is the organism with the largest wet-lab validated TRN, its set of interactions involves only ~50% of the repertoire of transcription factors currently known, and ~25% of its genes. Of...

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Detalles Bibliográficos
Autores principales: Veiga, Diogo FT, Vicente, Fábio FR, Nicolás, Marisa F, Vasconcelos, Ana Tereza R
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2453137/
https://www.ncbi.nlm.nih.gov/pubmed/18565227
http://dx.doi.org/10.1186/1471-2180-8-101

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2453137/
https://www.ncbi.nlm.nih.gov/pubmed/18565227
http://dx.doi.org/10.1186/1471-2180-8-101

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