Author

R. Ietswaart

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 Cell Biology· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:drug response / drug discovery· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

A. F. M. Dost· 1 shared A. Fekete· 1 shared A. L. Moye· 1 shared A. R. Baxter-Koenigs· 1 shared A. X. Chen· 1 shared B. Kim· 1 shared B. M. Smalec· 1 shared C. Aluya· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperCancer Biology

A. F. M. Dost

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3 papers

Recent·Most cited

Early-stage lung adenocarcinoma is driven by an injury-associated, plastic cell state dependent on a KRAS-ITGA3-SRC axis

A. L. Moye, A. F. M. Dost, R. Ietswaart, S. Sengupta, V. Ya, C. Aluya, C. G. Fahey, S. M. Louie, M. Paschini, C. F. Kim

This study identifies an injury-associated, plastic cell state in early-stage lung adenocarcinoma driven by the KRAS-ITGA3-SRC axis, showing its role in tumor initiation and progression.

bioRxiv · Feb 27, 2024Cancer Biology

A kinetic dichotomy between mitochondrial and nuclear gene expression drives OXPHOS biogenesis

E. McShane, M. Couvillion, R. Ietswaart, G. Prakash, B. M. Smalec, I. Soto, A. R. Baxter-Koenigs, K. Choquet, L. S. Churchman

The paper quantifies differences in nuclear and mitochondrial gene expression kinetics and identifies regulatory mechanisms underlying OXPHOS biogenesis.

bioRxiv · Feb 9, 2023Cell Biology

Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology

R. Ietswaart, S. Arat, A. X. Chen, S. Farahmand, B. Kim, W. DuMouchel, D. Armstrong, A. Fekete, J. J. Sutherland, L. Urban

The paper uses machine learning to link drug targets with adverse drug reactions using in vitro pharmacology data and FDA reports, identifying 221 target-ADR associations.

bioRxiv · Mar 12, 2020Pharmacology & Toxicology