Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response

MLA

M. D’Orazio, et al. “Machine Learning Phenomics (MLP) Combining Deep Learning with Time-Lapse-Microscopy for Monitoring Colorectal Adenocarcinoma Cells Gene Expression and Drug-Response.” Scientific Reports, vol. 12, no. 1, May 2022, pp. 1–14. EBSCOhost, https://doi.org/10.1038/s41598-022-12364-5.

APA

M. D’Orazio, M. Murdocca, A. Mencattini, P. Casti, J. Filippi, G. Antonelli, D. Di Giuseppe, M. C. Comes, C. Di Natale, F. Sangiuolo, & E. Martinelli. (2022). Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response. Scientific Reports, 12(1), 1–14. https://doi.org/10.1038/s41598-022-12364-5

Chicago

M. D’Orazio, M. Murdocca, A. Mencattini, P. Casti, J. Filippi, G. Antonelli, D. Di Giuseppe, et al. 2022. “Machine Learning Phenomics (MLP) Combining Deep Learning with Time-Lapse-Microscopy for Monitoring Colorectal Adenocarcinoma Cells Gene Expression and Drug-Response.” Scientific Reports 12 (1): 1–14. doi:10.1038/s41598-022-12364-5.