Machine learning approaches in microbiome research: challenges and best practices.

MLA

Papoutsoglou, Georgios, et al. “Machine Learning Approaches in Microbiome Research: Challenges and Best Practices.” Frontiers in Microbiology, vol. 14, Sept. 2023, p. 1261889. EBSCOhost, https://doi.org/10.3389/fmicb.2023.1261889.

APA

Papoutsoglou, G., Tarazona, S., Lopes, M. B., Klammsteiner, T., Ibrahimi, E., Eckenberger, J., Novielli, P., Tonda, A., Simeon, A., Shigdel, R., Béreux, S., Vitali, G., Tangaro, S., Lahti, L., Temko, A., Claesson, M. J., & Berland, M. (2023). Machine learning approaches in microbiome research: challenges and best practices. Frontiers in Microbiology, 14, 1261889. https://doi.org/10.3389/fmicb.2023.1261889

Chicago

Papoutsoglou, Georgios, Sonia Tarazona, Marta B Lopes, Thomas Klammsteiner, Eliana Ibrahimi, Julia Eckenberger, Pierfrancesco Novielli, et al. 2023. “Machine Learning Approaches in Microbiome Research: Challenges and Best Practices.” Frontiers in Microbiology 14 (September): 1261889. doi:10.3389/fmicb.2023.1261889.