Author

P. Jackson

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 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

A. Hawkins-Daarud· 1 shared A. Save· 1 shared C. Sauvey· 1 shared D. Boyett· 1 shared G. Ehrenkaufer· 1 shared H. Wang· 1 shared H. Yoon· 1 shared J. Blevitt· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperCancer Biology

A. Hawkins-Daarud

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Author profile →

2 papers

Recent·Most cited

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

H. Wang, M. G. Argenziano, H. Yoon, D. Boyett, A. Save, P. Petridis, W. Savage, P. Jackson, A. Hawkins-Daarud, N. Tran, L. Hu, O. Al-Dalahmah, J. N. Bruce, J. Grinband, K. R. Swanson, , J. Li

This paper develops BioNet, a biologically-informed deep learning model, to predict intratumoral heterogeneity in post-treatment glioblastoma using MRI and biopsy data, showing improved performance over existing methods.

npj Digital Medicine · Oct 19, 2024Peer-reviewedCancer Biology

High-throughput phenotypic screen identifies a new family of potent anti-amoebic compounds

C. Sauvey, G. Ehrenkaufer, J. Blevitt, P. Jackson, R. Abagyan

This paper identifies a new family of potent anti-amoebic compounds through high-throughput screening of a chemical library against Entamoeba histolytica.

bioRxiv · Oct 6, 2021Pharmacology & Toxicology