Author

G. Kutkaite

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 Immunology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 3 Organism:human· 3 Approach:statistical model· 3 Research Focus:drug response / drug discovery· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1

Frequent Co-Authors

M. P. Menden· 2 shared A. Boehner· 1 shared A. J. Ohnmacht· 1 shared A. Rajamani· 1 shared A. Schaebitz· 1 shared B. Fereydouni· 1 shared C. B. Schmidt-Weber· 1 shared C. Pilz· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersCancer Biology

M. P. Menden

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity

A. J. Ohnmacht, A. Rajamani, G. Avar, G. Kutkaite, E. Goncalves, D. Saur, M. P. Menden

The paper identifies DNA methylation biomarkers linked to drug sensitivity in cancer cell lines across multiple cancer types and drugs.

bioRxiv · Jun 1, 2023Cancer Biology

Integration of phenomics and transcriptomics data to reveal drivers of inflammatory processes in the skin

R. Batra, N. Garzorz-Stark, F. Lauffer, M. Jargosch, C. Pilz, S. Roenneberg, A. Schaebitz, A. Boehner, P. Seiringer, J. Thomas, B. Fereydouni, G. Kutkaite, M. Menden, L. C. Tsoi, J. E. Gudjonsson, , K. Eyerich

The paper integrates phenomics and transcriptomics data from skin samples to identify gene signatures driving inflammatory processes, revealing new factors like CEBPB and PTTG2.

bioRxiv · Jul 25, 2020 · PreprintImmunology

A statistical framework for assessing pharmacological response and biomarkers using uncertainty estimates

D. Wang, J. Hensman, G. Kutkaite, T. S. Toh, GDSC Screening Team, J. R. Dry, J. Saez-Rodriguez, M. Garnett, M. P. Menden, F. Dondelinger

The paper introduces a statistical framework using uncertainty estimates to identify biomarkers from drug screening data, finding 24 known and 6 novel biomarkers in cancer cell lines.

bioRxiv · May 1, 2020 · PreprintCancer Biology