Author

P. K. Rogan

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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Pharmacology & Toxicology· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Organism:human· 2 Approach:machine learning (classical)· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

E. J. Mucaki· 2 shared A. J. Bagchee-Clark· 1 shared D. Lizotte· 1 shared J. Z. L. Zhao· 1 shared T. Whitehead· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 6 mutual co-author links

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2 shared papersPharmacology & Toxicology

E. J. Mucaki

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2 papers

Recent·Most cited

Pharmacology & ToxicologybioRxivNov 13, 2020

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors

A. J. Bagchee-Clark, E. J. Mucaki, T. Whitehead, P. K. Rogan

This paper develops pathway-extended gene expression signatures using machine learning to predict patient responses to kinase inhibitors with improved accuracy.

DOI 10.1002/mco2.46

humanbulk RNA-seq

𝕏 PostBluesky

Pharmacology & ToxicologySignal Transduction and Targeted TherapyPeer-reviewedJan 11, 2019

Predicting Response to Platin Chemotherapy Agents with Biochemically-inspired Machine Learning

E. J. Mucaki, J. Z. L. Zhao, D. Lizotte, P. K. Rogan

The paper develops gene signatures for predicting response to platinum-based chemotherapy drugs using machine learning and validates them in cancer patient data.

DOI 10.1038/s41392-018-0034-5

humanbulk RNA-seq

𝕏 PostBluesky