Author

S. Pasetto

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· 3

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:differential expression· 2 Research Focus:benchmarking· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

H. Enderling· 2 shared R. Gatenby· 2 shared A. M. Forero Pinto· 1 shared A. P. Gomes· 1 shared A. Schultz· 1 shared D. Ilter· 1 shared E. Scanu· 1 shared F. M. Joaquim· 1 shared

Activity by Year

2022-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersCancer Biology

H. Enderling

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Interactions between ploidy and resource availability shape clonal interference at initiation and recurrence of glioblastoma

Z. Nowicka, F. Rentzeperis, R. Beck, V. Tagal, A. M. Forero Pinto, E. Scanu, T. Veith, J. Cole, D. Ilter, W. Dominguez Viqueira, J. K. Teer, K. Maksin, S. Pasetto, M. A. Abdalah, G. Fiandaca, , N. Andor

This study uses a mathematical model to show that ploidy and resource availability in the tumor microenvironment influence glioblastoma initiation and recurrence.

bioRxiv · Oct 17, 2023 · PreprintCancer Biology

Logistic tumor-population growth and ghost-points symmetry

S. Pasetto, I. Harshe, R. Brady, R. Gatenby, H. Enderling

This paper introduces a method using logistic function symmetry to estimate tumor growth parameters from limited data, achieving faster and more accurate results than conventional regression approaches.

bioRxiv · Aug 30, 2023 · PreprintCancer Biology

Breast Cancer Reaction-Diffusion from Spectral-Spatial Analysis in Immunohistochemistry

S. Pasetto, M. U. Zahid, R. Diaz, M. Montejo, M. Rosa, R. Gatenby, H. Enderling

The paper uses spatial-spectral analysis of immunohistochemistry data to model tumor growth dynamics via reaction-diffusion equations in breast cancer patients.

bioRxiv · Jul 10, 2022 · PreprintCancer Biology