Author

D. C. Koestler

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· 1 Microbiology· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:human· 2 Approach:Bayesian inference· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:differential expression· 1 Research Focus:metabolism & bioenergetics· 1 Assay:metabolomics· 1

Frequent Co-Authors

C. A. Banks· 1 shared C. A. Manton· 1 shared C. S. McCoin· 1 shared D. R. Hurst· 1 shared D. R. Welch· 1 shared D. S. Michaud· 1 shared E. M. M. Morris· 1 shared J. A. Allen· 1 shared

Activity by Year

2019-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 13 mutual co-author links

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1 shared paperCancer Biology

C. A. Banks

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Perturbation of BRMS1 interactome reveals pathways that impact cell migration

R. C. Zimmermann, M. E. Sardiu, C. A. Manton, M. S. Miah, C. A. Banks, M. K. Adams, D. C. Koestler, D. R. Hurst, M. D. Edmonds, M. P. Washburn, D. R. Welch

This study identifies BRMS1 interactions and phosphorylation events that influence cell migration and metastasis in breast cancer.

bioRxiv · Feb 4, 2021 · PreprintCancer Biology

Divergent Energy Expenditure Impacts Mouse Metabolic Adaptation to Acute High-Fat/High-Sucrose Diet Producing Sexually Dimorphic Weight Gain Patterns

E. M. M. Morris, R. D. Noland, J. A. Allen, C. S. McCoin, Q. Xia, D. C. Koestler, R. P. Shook, J. R. B. Lighton, J. A. Christianson, J. P. Thyfault

This study shows that differences in energy expenditure due to ambient temperature and sex affect metabolic adaptation to a high-fat/high-sucrose diet, leading to sexually dimorphic weight gain patterns in mice.

bioRxiv · Nov 13, 2019Physiology

A Bayesian framework for identifying consistent patterns of microbial abundance between body sites

R. Meier, J. A. Thompson, M. Chung, N. Zhao, K. T. Kelsey, D. S. Michaud, D. C. Koestler

The paper introduces a Bayesian framework to identify microbes with consistent abundance patterns between body sites related to a phenotypic variable, demonstrating its effectiveness using pancreatic cancer patient data.

bioRxiv · Jun 18, 2019Microbiology