Author

S. M. Roth

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 Ecology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

A. D. Mays· 1 shared A. J. Kiliti· 1 shared A. P. McDeed· 1 shared A. Quintin· 1 shared A. T. Riegel· 1 shared A. Wellstein· 1 shared D. M. Aebersold· 1 shared E. Ballew· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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Curved chords = mutual co-authorship

1 shared paperCancer Biology

A. D. Mays

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

HPV and p53 status as precision determinants of head and neck cancer response to DNA-PKcs inhibition in combination with irradiation

L. Hayrapetyan, S. M. Roth, L. Hovhannisyan, M. Medo, A. Quintin, J. Ott, J. Albers, D. M. Aebersold, Y. Zimmer, M. Medova

bioRxiv · Nov 2, 2023Cancer Biology

Cell-free, methylated DNA in blood samples reveals tissue-specific, cellular damage from radiation treatment

M. E. Barefoot, N. Loyfer, A. J. Kiliti, M. O. Schmidt, S. Shabi-Porat, S. Jain, S. M. Roth, A. P. McDeed, N. Shahrour, E. Ballew, Y.-T. Lin, H.-H. Li, A. D. Mays, S. Rudra, A. T. Riegel, , A. Wellstein

This study uses cell-free methylated DNA in blood to detect tissue-specific damage from radiation treatment in mice and cancer patients.

bioRxiv · Apr 12, 2022Cancer Biology

Predicting suitability of regions for Zika outbreaks with zero-inflated models trained using climate data

S. M. Roth, M. I. Teboh-Ewungkem, M. Li

This paper uses zero-inflated models to predict future Zika outbreak suitability based on climate data and finds most regions will become more suitable under extreme climate change scenarios.

bioRxiv · Sep 16, 2019 · PreprintEcology