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Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics data
Characterisation of gene-regulatory network (GRN) interactions provides a stepping stone to understanding how genes affect cellular phenotypes. Yet, despite advances in profiling technologies, GRN reconstruction from gene expression data remains a pressing problem in systems biology. Here, we devise...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327016/ https://www.ncbi.nlm.nih.gov/pubmed/32606380 http://dx.doi.org/10.1038/s41540-020-0140-1 |