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A Bayesian data fusion based approach for learning genome-wide transcriptional regulatory networks
BACKGROUND: Reverse engineering of transcriptional regulatory networks (TRN) from genomics data has always represented a computational challenge in System Biology. The major issue is modeling the complex crosstalk among transcription factors (TFs) and their target genes, with a method able to handle...
Autores principales: | Sauta, Elisabetta, Demartini, Andrea, Vitali, Francesca, Riva, Alberto, Bellazzi, Riccardo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7257163/ https://www.ncbi.nlm.nih.gov/pubmed/32471360 http://dx.doi.org/10.1186/s12859-020-3510-1 |
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