Author

Gozde N. Gunesli

University of WarwickORCID 0000-0002-1008-328XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:clustering· 1 Research Focus:differential expression· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Lawrence S. YoungiD· 2 shared Nasir RajpootiD· 2 shared Fayyaz MinhasiD· 1 shared Heidi LyngiD· 1 shared Kari-Anne Frikstad Valen· 1 shared Muhammad DawoodiD· 1 shared Ruoyu WangiD· 1 shared Shan E Ahmed RazaiD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 24 mutual co-author links

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2 shared papersCancer Biology

Lawrence S. YoungORCID

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2 papers

Recent·Most cited

Cancer BiologybioRxivPreprintNov 7, 2025

Star-Motifs: Revealing Single-Cell Spatiotypes from Routine Histology Using Star-Convex Neighborhoods

Gozde N. Gunesli, Muhammad Dawood, Lawrence S. Young…·Nasir Rajpoot

Star-Motifs identifies spatial patterns in histology slides to reveal clinically relevant tumor microenvironment features and survival correlations.

DOI 10.1101/2025.11.07.687248

humanspatial transcriptomics

𝕏 PostBluesky

Pathologynpj Precision OncologyPeer-reviewedJan 11, 2025

A Deep Learning Framework for Predicting Prognostically Relevant Consensus Molecular Subtypes in HPV-Positive Cervical Squamous Cell Carcinoma from Routine Histology Images

Ruoyu Wang, Gozde N. Gunesli, Vilde Eide Skingen…·Nasir Rajpoot

This paper develops a deep learning framework to predict consensus molecular subtypes in HPV-positive cervical cancer from histology images, showing significant survival stratification and TME differences between subtypes.

11 citations

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