Supervised Machine Learning Enables Geospatial Microbial Provenance

The recent increase in publicly available metagenomic datasets with geospatial metadata has made it possible to determine location-specific, microbial fingerprints from around the world. Such fingerprints can be useful for comparing microbial niches for environmental research, as well as for applica...

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Detalles Bibliográficos
Autores principales: Bhattacharya, Chandrima, Tierney, Braden T., Ryon, Krista A., Bhattacharyya, Malay, Hastings, Jaden J. A., Basu, Srijani, Bhattacharya, Bodhisatwa, Bagchi, Debneel, Mukherjee, Somsubhro, Wang, Lu, Henaff, Elizabeth M., Mason, Christopher E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601318/
https://www.ncbi.nlm.nih.gov/pubmed/36292799
http://dx.doi.org/10.3390/genes13101914

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601318/
https://www.ncbi.nlm.nih.gov/pubmed/36292799
http://dx.doi.org/10.3390/genes13101914

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