Author

V. Adhikarla

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 Immunology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:cell signaling & trafficking· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

C. E. Brown· 2 shared D. Abler· 2 shared D. Maestrini· 2 shared H. Cho· 2 shared P. Sahoo· 2 shared R. C. Rockne· 2 shared S. Branciamore· 2 shared A. B. Brummer· 1 shared

Activity by Year

2017-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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2 shared papersCancer Biology

C. E. Brown

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Author profile →

4 papers

Recent·Most cited

Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables

A. B. Brummer, A. Xella, R. Woodall, V. Adhikarla, H. Cho, M. B. Gutova, C. E. Brown, R. C. Rockne

This paper applies sparse identification of non-linear dynamics (SINDy) to discover and interpret CAR T-cell interaction dynamics with glioblastoma cells using latent variables.

bioRxiv · Sep 22, 2022Cancer Biology

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

P. Sahoo, X. Yang, D. Abler, D. Maestrini, V. Adhikarla, D. Frankhouser, H. Cho, V. Machuca, D. Wang, M. Barish, M. Gutova, S. Branciamore, C. E. Brown, R. C. Rockne

This paper uses a mathematical model to analyze CAR T-cell killing dynamics in glioma, showing dose-dependent effects on proliferation and exhaustion.

bioRxiv · Nov 9, 2019Immunology

Connecting the Microenvironmental Niche to Treatment Response in Ovarian Cancer

M. Strobl, M. Wicker, V. Adhikarla, A. Shockey, E. Lakatos, P. Pooladvand, R. Schenck, L. Saputro, C. Gatenby, M. Koppens, S. Cruz Garcia, R. Wenham, M. Damaghi, J. A. Gallaher

This study develops a mathematical model to analyze spatial interactions in ovarian cancer microenvironments and shows how niche composition affects treatment response.

bioRxiv · Oct 24, 2018 · PreprintCancer Biology

Aging in a relativistic biological space-time

D. Maestrini, D. Abler, V. Adhikarla, S. Armenian, S. Branciamore, N. Carlesso, G. Marcucci, Y.-H. Kuo, P. Sahoo, R. Rockne

This paper proposes a theoretical framework modeling biological aging as trajectories in a mathematical space-time, with applications to cancer and aging rates.

bioRxiv · Dec 5, 2017Cancer Biology