Author

G. Atwal

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· 2

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Approach:deep learning· 1 Assay:imaging· 1 Research Focus:spatial domain detection· 1 Approach:statistical model· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

A. Danyi· 1 shared A. Rosario· 1 shared C. C. Yu· 1 shared C. van Herpen· 1 shared D. Schmolze· 1 shared E. Cuppen· 1 shared G. Getz· 1 shared H. Levine· 1 shared

Activity by Year

2019-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperCancer Biology

A. Danyi

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2 papers

Recent·Most cited

Fractal dimension, occupancy and hotspot analyses of B cell spatial distribution predict clinical outcome in breast cancer

J. C. Wortman, T.-F. He, S. Solomon, R. Z. Zhang, A. Rosario, R. Wang, T. Y. Tu, D. Schmolze, Y. Yuan, S. E. Yost, X. Li, H. Levine, G. Atwal, P. P. Lee, C. C. Yu

The paper analyzes the spatial distribution of B cells in breast cancer tumors using novel statistical methods and finds that their spatial arrangement correlates with clinical outcomes.

bioRxiv · Jun 21, 2019 · PreprintCancer Biology

A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations

W. Jiao, G. Atwal, P. Polak, R. Karlic, E. Cuppen, A. Danyi, J. de Ridder, C. van Herpen, M. P. Lolkema, N. Steeghs, G. Getz, Q. D. Morris, L. D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net

This paper develops a deep learning classifier using whole genome sequencing data to distinguish cancer types and identify metastatic origins.

bioRxiv · Jan 22, 2019 · PreprintCancer Biology