Author

D. S. Tadele

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 Evolutionary Biology· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Assay:bulk RNA-seq· 2 Organism:human· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:deconvolution· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:ecology & biodiversity· 1

Frequent Co-Authors

J. G. Scott· 3 shared J. M. Enserink· 2 shared J. Maltas· 2 shared M. Hinczewski· 2 shared A. Durmaz· 1 shared A. Frigessi· 1 shared A. Köhn-Luque· 1 shared B.-T. Gjertsen· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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3 shared papersEvolutionary Biology

J. G. Scott

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Author profile →

5 papers

Recent·Most cited

Frequency-dependent ecological interactions increase the prevalence and shape the distribution of pre-existing drug resistance

J. Maltas, D. S. Tadele, A. Durmaz, C. D. McFarland, M. Hinczewski, J. G. Scott

This study shows frequency-dependent ecological interactions help pre-existing drug resistance persist despite fitness costs, using simulations and engineered mutants in NSCLC.

bioRxiv · Mar 16, 2023 · PreprintEvolutionary Biology

Hidden Interactions: Frequency-Dependence Emulates Selection-Driven Dynamics in Evolving Populations

R. J. Barker-Clarke, J. A. Pachter, J. M. Gray, S. Leither, M. A. R. Strobl, D. S. Tadele, J. Maltas, M. Hinczewski, J. G. Scott

This paper shows that frequency-dependent interactions can mask or mimic frequency-independent selection in evolving populations, emphasizing the need to account for interactions in evolutionary inference.

bioRxiv · Mar 15, 2023 · PreprintEvolutionary Biology

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems

S. Hamis, P. Somervuo, J. A. Agren, D. S. Tadele, J. Kesseli, J. G. Scott, M. Nykter, P. Gerlee, D. Finkelshtein, O. Ovaskainen

This paper introduces spatial cumulant models to analyze and improve treatment strategies for cancer cell populations modeled as spatio-temporal point processes.

bioRxiv · May 7, 2022Cancer Biology

Phenotypic deconvolution in heterogeneous cancer cell populations using drug screening data

A. Köhn-Luque, E. M. Myklebust, D. S. Tadele, M. Giliberto, L. Schmiester, J. Noory, E. Harivel, P. Arsenteva, S. M. Mumenthaler, F. Schjesvold, K. Tasken, J. M. Enserink, K. Leder, A. Frigessi, J. Foo

This paper introduces PhenoPop, a method to deconvolve tumor heterogeneity using drug screening data, identifying subpopulations with differential drug responses and their frequencies.

bioRxiv · Jan 17, 2022Cancer Biology

A cell competition-based drug screen identifies a novel compound that induces dual c-Myc depletion and p53 activation

D. S. Tadele, J. M. Robertson, R. Crispin, M. C. Herrera, M. Chlubnova, L. I. Piechaczyk, P. Ayuda-Duran, S. K. Singh, T. Gedde-Dahl, Y. Floisand, J. Skavland, J. Wesche, B.-T. Gjertsen, J. M. Enserink

This study identifies a novel compound, DJ34, that depletes c-Myc and activates p53, showing strong activity against leukemic stem cells across multiple cancer types.

bioRxiv · May 16, 2020 · PreprintCancer Biology