PhD in machine learning applied to bioinformatics.
Granada (Spain)
carrilloperezfrancisco at gmail dot com
pacocp pacocp9 franciscocpClick here for all publications
Carrillo-Perez, F., Zheng, Y., Nandi, T.N., Madduri, R., Shen, J., and Gevaert, O. (2023)
Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models.
Nature Biomedical Engineering, https://doi.org/10.1038/s41551-024-01193-8,
[Paper,
Code]
Carrillo-Perez, F., Pizurica, M., Ozawa, M., Vogel, H., West, R., Kong, C., Herrera, L.J., Shen, J., Gevaert, O. (2023)
Synthetic whole-slide image tile generation with gene expression profile-infused deep generative models.
Cell Reports Methods, https://doi.org/10.1016/j.crmeth.2023.100534,
[Paper,
Code]
Carrillo-Perez, F., Morales JC, Castillo-Secilla D, Gevaert O, Rojas I, Herrera LJ. (2022)
Machine-Learning-Based Late Fusion on Multi-Omics and Multi-Scale Data for Non-Small-Cell Lung Cancer Diagnosis.
Journal of Personalized Medicine, 12(4), 601, https://doi.org/10.3390/jpm12040601
[Paper,
Code]
Carrillo-Perez, F., Morales, J. C., Castillo-Secilla, D., Molina-Castro, Y.,
Guillén, A., Rojas, I., & Herrera, L. J. (2021)
Non-small-cell lung cancer classification via RNA-Seq and histology imaging probability fusion.
BMC bioinformatics, 22(1), 1-19, https://doi.org/10.1007/s00521-020-05679-9
[Paper,
Code]
Carrillo-Perez, F., Herrera, L. J., Carceller, J. M.,
& Guillén, A. (2021).
Deep learning to classify ultra-high-energy cosmic rays by means of PMT signals.
Neural Computing and Applications., 1-17, https://doi.org/10.1007/s00521-020-05679-9
[Paper,
Code]