Author

Ellen L. Barlow

UNSW SydneyORCID 0000-0001-7864-1252Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Caroline Elizabeth FordiD· 2 shared Dongli LiuiD· 2 shared Elyse Powell· 2 shared Kristina WartoniD· 2 shared Marilisa CortesiiD· 2 shared Emanuele� GiordanoiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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2 shared papersBioengineering

Caroline Elizabeth FordORCID

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2 papers

Recent·Most cited

BioengineeringBioengineering & Translational MedicinePeer-reviewedOct 6, 2025

Development and validation of a computational tool to predict treatment outcomes in cells from High-Grade Serous Ovarian Cancer patients

Marilisa Cortesi, Dongli Liu, Elyse Powell…·Caroline Elizabeth Ford

The paper develops and validates a computational tool to predict treatment outcomes in HGSOC cells, showing its potential for preclinical research and personalized medicine.

1 citation

humanbulk RNA-seq

𝕏 PostBluesky

BioengineeringAdvanced BiologyPeer-reviewedAug 12, 2024

Accurate identification of cancer cells in complex pre-clinical models using deep-learning: a transfection free approach.

Marilisa Cortesi, Dongli Liu, Elyse Powell…·Caroline Elizabeth Ford

ORACLE, a deep-learning model, accurately identifies ovarian cancer cells from healthy cells in 3D co-cultures using nuclear shape, outperforming existing methods.

4 citations

humanimaging

𝕏 PostBluesky