Author

S. Prabhakaran

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· 4 Bioengineering· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 5 Research Focus:cell type annotation· 4 Research Focus:clustering· 4 Approach:deep learning· 4 Organism:human· 3 Assay:imaging· 3 Research Focus:spatial domain detection· 2 Approach:Bayesian inference· 1

Frequent Co-Authors

A. R. A. Anderson· 3 shared M. Robertson-Tessi· 3 shared A. A. Beg· 2 shared C. Gatenbee· 2 shared R. A. Gatenby· 2 shared S. Antonia· 2 shared A. E. Cornish· 1 shared A. J. Carr· 1 shared

Activity by Year

2018-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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3 shared papersCancer Biology

A. R. A. Anderson

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Author profile →

6 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

PhysiCOOL: A generalized framework for model Calibration and Optimization Of modeLing projects

I. G. Goncalves, D. A. Hormuth, S. Prabhakaran, C. M. Phillips, J. M. Garcia-Aznar

PhysiCOOL provides an open-source Python library for calibrating and optimizing PhysiCell models without requiring high-performance computing.

bioRxiv · Nov 17, 2022Bioengineering

Distinct tumor-immune ecologies in NSCLC patients predict progression and define a clinical biomarker of therapy response

S. Prabhakaran, C. Gatenbee, M. Robertson-Tessi, J. Gray, S. Antonia, A. A. Beg, R. A. Gatenby, A. R. A. Anderson

The paper analyzes multiplexed histological images from NSCLC patients to identify spatial immune ecologies that predict disease progression and serve as potential biomarkers for therapy response.

bioRxiv · Oct 22, 2022 · PreprintCancer Biology

VALIS: Virtual Alignment of pathoLogy Image Series

C. D. Gatenbee, A.-M. Baker, S. Prabhakaran, R. J. C. Slebos, G. Mandal, E. Mulholland, S. Leedham, J. R. Conejo-Garcia, C. H. Chung, M. Robertson-Tessi, T. A. Graham, A. R. A. Anderson

VALIS automates registration of immunohistochemistry and immunofluorescence images, enabling spatial analysis of whole slide images with low error and minimal computational time.

bioRxiv · Nov 9, 2021 · PreprintCancer Biology

Mistic: an open-source multiplexed image t-SNE viewer

S. Prabhakaran, C. Gatenbee, M. Robertson-Tessi, J. West, A. A. Beg, J. E. Gray, S. Antonia, R. A. Gatenby, A. R. A. Anderson

Mistic provides an open-source tool to visualize multiplexed images using t-SNE or UMAP layouts for exploratory analysis of tumor tissue ecology.

bioRxiv · Oct 8, 2021Cancer Biology

Single-cell Map of Diverse Immune Phenotypes Driven by the Tumor Microenvironment

E. Azizi, A. J. Carr, G. Plitas, A. E. Cornish, C. Konopacki, S. Prabhakaran, J. Nainys, K. Wu, V. Kiseliovas, M. Setty, K. Choi, R. M. Fromme, P. Dao, P. T. McKenney, R. C. Wasti, , D. Pe'er

The paper maps immune cell phenotypes in breast cancer using single-cell RNA-seq and identifies continuous tumor-specific expansions driven by environmental cues.

bioRxiv · Apr 2, 2018Immunology