Author

E. F. Douglass

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Biology Disciplines

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Cancer Biology· 2

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

A. Califano· 2 shared C. Karan· 2 shared R. Realubit· 2 shared A. Fernandez-Torras· 1 shared A. Mitrofanova· 1 shared A. Pessia· 1 shared A. Rodriguez-Calero· 1 shared A. Vasciaveo· 1 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersCancer Biology

A. Califano

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2 papers

Recent·Most cited

OncoLoop: A network-based precision cancer medicine framework

A. Vasciaveo, M. Zou, J. M. Arriaga, F. Geraldes de Almeida, E. F. Douglass, M. Shibata, A. Rodriguez-Calero, S. de Brot, A. Mitrofanova, C. W. Chua, C. Karan, R. Realubit, S. Y. Pampou, J. Y. Kim, E. Corey, , C. Abate-Shen

OncoLoop predicts and validates drug sensitivity in tumors and their models by leveraging perturbational profiles of oncology drugs, showing success in prostate cancer models and patient cohorts.

bioRxiv · Feb 11, 2022Cancer Biology

A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

E. F. Douglass, R. J. Allaway, B. Szalai, W. Wang, T. Tian, A. Fernandez-Torras, R. Realubit, C. Karan, S. Zheng, A. Pessia, Z. Tanoli, M. Jafari, F. Wan, S. Li, Y. Xiong, , A. Califano

The paper hosts a DREAM Challenge to evaluate computational models for predicting drug polypharmacology using perturbational profile data from 32 kinase inhibitors.

bioRxiv · Dec 21, 2020Cancer Biology