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ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks
BACKGROUND: Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN...
Autores principales: | Chávez Montes, Ricardo A, Coello, Gerardo, González-Aguilera, Karla L, Marsch-Martínez, Nayelli, de Folter, Stefan, Alvarez-Buylla, Elena R |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4021103/ https://www.ncbi.nlm.nih.gov/pubmed/24739361 http://dx.doi.org/10.1186/1471-2229-14-97 |
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