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SCOUR: a stepwise machine learning framework for predicting metabolite-dependent regulatory interactions
BACKGROUND: The topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms—two characteristics that make it difficult to model...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8268592/ https://www.ncbi.nlm.nih.gov/pubmed/34238207 http://dx.doi.org/10.1186/s12859-021-04281-7 |