Author

R. Carelli

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

M. Loda· 2 shared M. Omar· 2 shared B. D. Robinson· 1 shared C. Abate-Shen· 1 shared C. E. Barbieri· 1 shared C. Fidalgo-Ribeiro· 1 shared C. Unkenholz· 1 shared D. Brundage· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersCancer Biology

M. Loda

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Distinct mesenchymal cell states mediate prostate cancer progression

H. Pakula, M. Omar, R. Carelli, F. Pederzoli, G. N. Fanelli, T. Pannellini, L. Van Emmenis, S. Rodrigues, C. Fidalgo-Ribeiro, P. V. Nuzzo, N. J. Brady, M. Jere, C. Unkenholz, M. K. Alexanderani, F. Khani, , M. Loda

This study identifies distinct mesenchymal cell states in prostate cancer stroma that correlate with metastatic progression and develops a gene signature to predict patient outcomes.

bioRxiv · Mar 29, 2023Cancer Biology

Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology

J. Rosenthal, R. Carelli, M. Omar, D. Brundage, H. Ella, J. Nyman, S. Hari, E. M. Van Allen, M. Luigi, R. Umeton, M. Loda

The paper introduces PathML, a computational pathology toolkit designed for scalability, standardization, and ease of use in cancer research, with applications demonstrated across diverse use-cases.

bioRxiv · Oct 21, 2021Cancer Biology