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Globally learning gene regulatory networks based on hidden atomic regulators from transcriptomic big data
BACKGROUND: Genes are regulated by various types of regulators and most of them are still unknown or unobserved. Current gene regulatory networks (GRNs) reverse engineering methods often neglect the unknown regulators and infer regulatory relationships in a local and sub-optimal manner. RESULTS: Thi...
| Autores principales: | , , , , , , |
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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/PMC7559338/ https://www.ncbi.nlm.nih.gov/pubmed/33054712 http://dx.doi.org/10.1186/s12864-020-07079-8 |