Cargando…
Machine learning-assisted single-cell Raman fingerprinting for in situ and nondestructive classification of prokaryotes
Accessing enormous uncultivated microorganisms (microbial dark matter) in various Earth environments requires accurate, nondestructive classification, and molecular understanding of the microorganisms in in situ and at the single-cell level. Here we demonstrate a combined approach of random forest (...
| Autores principales: | , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2021
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8397914/ https://www.ncbi.nlm.nih.gov/pubmed/34485857 http://dx.doi.org/10.1016/j.isci.2021.102975 |