Author

Jill Carol Rubinstein

1The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut.ORCID 0000-0002-1222-8657Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1 Immunology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Organism:human· 4 Research Focus:cell type annotation· 3 Approach:deep learning· 3 Assay:imaging· 3 Organism:mouse· 3 Assay:spatial transcriptomics· 3 Research Focus:clustering· 2 Research Focus:differential expression· 2

Frequent Co-Authors

Jeffrey H. ChuangiD· 4 shared Meenhard HerlyniD· 3 shared Sergii DomanskyiiD· 3 shared Todd B. SheridaniD· 3 shared Haiyin LiiD· 2 shared Jessica KasteriD· 2 shared Abate Assefa BashawiD· 1 shared Adam H. ThieseniD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersBioinformatics

Jeffrey H. ChuangORCID

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Author profile →

5 papers

Recent·Most cited

Tumor cell-intrinsic mtDNA instability drives cGAS-dependent temporal remodeling of the melanoma immune microenvironment

Abate Assefa Bashaw, Ashley D. Winters, Yuanjiu Lei, Luiza Ferreira Araujo, Do Gia Tam Vo, Arunachalam Sekar, John F. Bachman, Paige S Graves, Melissa Pineda, Jill Carol Rubinstein, Gerald S. Shadel, Marcus Bosenberg, Laura Ciaccia West, Andrew Phillip West

This study shows that tumor cell-intrinsic mtDNA instability drives temporal changes in the melanoma immune microenvironment through cGAS, affecting immune cell states and therapeutic response.

bioRxiv · Sep 30, 2026 · PreprintImmunology

DIANNE: Segmentation-Free Localization of Histology Differential Attributes

Sergii Domanskyi, Jill Carol Rubinstein, Todd Sheridan, Adam H. Thiesen, Javad Noorbakhsh, Juliana Alcoforado Diniz, Ramalakshmi Ramasamy, Dylan S. Baker, Riley Sheldon, Qian Wu, George A. Kuchel, Nicolas Musi, Sara E Espinoza, Francisco G. Cigarroa, Paul Robson, Jeffrey H. Chuang

DIANNE enables rapid training and inference of spatial differential attributes in histology images without manual annotations, using mixup augmentation and foundation models.

bioRxiv · Jul 23, 2026 · PreprintPathology

Nextflow Pipeline for Visium and H&E Data from Patient-Derived Xenograft Samples

Sergii Domanskyi, Anuj Srivastava, Jessica Kaster, Haiyin Li, Meenhard Herlyn, Jill Carol Rubinstein, Jeffrey H. Chuang

The paper develops a Nextflow pipeline for processing Visium spatial transcriptomics and H&E images from PDX samples, enabling multi-modal analysis and integration of spatial gene expression and morphometric features.

Cell Reports Methods · Apr 15, 2024Peer-reviewedBioinformatics

Spatiotemporal profiling defines persistence and resistance dynamics during targeted treatment of melanoma

Jill C. Rubinstein, Sergii Domanskyi, Todd B. Sheridan, Brian Sanderson, SungHee Park, Jessica Kaster, Haiyin Li, Olga Anczukow, Meenhard Herlyn, Jeffrey H. Chuang

This study uses spatial transcriptomics and deep learning to analyze melanoma treatment resistance, identifying persister states and resistance mechanisms with spatiotemporal resolution.

bioRxiv · Feb 2, 2024Cancer Biology

A pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis

Brian S. White, X. Woo, Soner Koc, Todd Sheridan, Steven B. Neuhauser, Shidan Wang, Yvonne A. Evrard, John David Landua, R. Jay Mashl, Sherri R. Davies, Bingliang Fang, Maria Gabriela Raso, Kurt W. Evans, Matthew H. Bailey, Yeqing Chen, , Jeffrey H. Chuang

The paper presents a pan-cancer PDX histology image repository with genomic and pathological annotations for deep learning analysis of tumor regions and xenograft-transplant lymphoproliferative disorder prediction.

bioRxiv · Oct 26, 2022 · PreprintBioinformatics