Author

Ginte Kutkaite

Helmholtz MunichORCID 0000-0002-2918-294XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:drug response / drug discovery· 2 Approach:deep learning· 1 Approach:statistical model· 1

Frequent Co-Authors

Diyuan LuiD· 2 shared Michael P. MendeniD· 2 shared Alexander J. OhnmachtiD· 1 shared Daksh P.S. Pamar· 1 shared Daniel KrappmanniD· 1 shared Göksu AvariD· 1 shared Thomas J. O’NeilliD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 15 mutual co-author links

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2 shared papersCancer Biology

Diyuan LuORCID

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2 papers

Recent·Most cited

Systematic identification of pan-cancer single-gene expression biomarkers in drug high-throughput screens

Ginte Kutkaite, Göksu Avar, Diyuan Lu, Thomas J. O’Neill, Daniel Krappmann, Michael P. Menden

The paper develops a regression framework to identify pan-cancer single-gene biomarkers of drug sensitivity in cell line screens, recovering known markers and identifying new ones for ERK/MAPK inhibitors.

PLoS ONE · May 11, 2026Peer-reviewedCancer Biology

Enhancing Gene Expression Representation and Drug Response Prediction with Data Augmentation and Gene Emphasis

Diyuan Lu, Daksh P.S. Pamar, Alexander J. Ohnmacht, Ginte Kutkaite, Michael P. Menden

This paper introduces GExMix, a data augmentation method for gene expression data, which improves drug response prediction by enhancing representation learning and prioritizing gene-centric information.

bioRxiv · May 15, 2024 · PreprintBioinformatics