Author

D. Maestrini

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 Cell Biology· 1 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 Approach:biophysical modeling· 1 Assay:ChIP-seq· 1 Research Focus:chromatin & epigenetic regulation· 1

Frequent Co-Authors

S. Branciamore· 3 shared D. Abler· 2 shared D. Frankhouser· 2 shared G. Marcucci· 2 shared N. Carlesso· 2 shared P. Sahoo· 2 shared R. C. Rockne· 2 shared V. Adhikarla· 2 shared

Activity by Year

2017-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersCancer Biology

S. Branciamore

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Author profile →

4 papers

Recent·Most cited

Xist-seeded nucleation sites form local concentration gradients of silencing proteins to inactivate the X-chromosome

Y. Markaki, J. G. Chong, C. Luong, S. Y. X. Tan, Y. Wang, E. C. Jacobson, D. Maestrini, I. Dror, B. A. Mistry, J. Schoeneberg, A. Banerjee, M. Guttman, T. Chou, K. Plath

This study identifies Xist-seeded nucleation sites that create local concentration gradients of silencing proteins, leading to X-chromosome inactivation through macromolecular crowding.

bioRxiv · Nov 22, 2020Cell 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

State-Transition Analysis of Time-Sequential Gene Expression Identifies Critical Points That Predict Leukemia Development

R. C. Rockne, S. Branciamore, J. Qi, D. Frankhouser, D. O'Meally, W.-K. Hua, G. J. Cook, L. Zhang, E. Carnahan, A. Marom, H. Wu, D. Maestrini, X. Wu, Y.-C. Yuan, Z. Liu, , G. Marcucci

The paper models leukemia transcriptome dynamics in a state-space to identify critical points that predict disease development.

bioRxiv · Jun 4, 2019 · 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