Author

Ryan Preska

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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Bioinformatics· 2 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 3 Organism:human· 3 Research Focus:cell type annotation· 2 Research Focus:cell-cell communication· 2 Research Focus:spatial domain detection· 2 Assay:spatial transcriptomics· 2 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Aaron T. MayeriD· 3 shared Alexandro E. TrevinoiD· 3 shared H. Blaize D’AngioiD· 3 shared Zhenqin WuiD· 3 shared Ann Marie EgloffiD· 2 shared Eric WuiD· 2 shared Gregory W. CharvilleiD· 2 shared Honesty KimiD· 2 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBioinformatics

Aaron T. MayerORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Spatial proteomics of human diabetic kidney disease, from health to class III

Ayano Kondo, Monee McGrady, Dhiraj Nallapothula, Hira Ali, Alexandro E. Trevino, A. M. Lam, Ryan Preska, H. Blaize D’Angio, Zhenqin Wu, Lauren N. Lopez, Harshanna Badhesha, Chenoa R. Vargas, Achyuta Ramesh, Nasim Wiegley, Seung Seok Han, , Maryam Afkarian

The paper uses spatial proteomics to analyze protein expression changes in human diabetic kidney disease across different stages, revealing compartment-specific cellular and inflammatory changes.

Diabetologia · Jul 22, 2024Peer-reviewedMolecular Biology

7-UP: generating in silico CODEX from a small set of immunofluorescence markers

Eric Wu, Alexandro E. Trevino, Zhenqin Wu, Kyle Swanson, Honesty Kim, H. Blaize D’Angio, Ryan Preska, Aaron E. Chiou, Gregory W. Charville, Piero D. Dalerba, Umamaheswar Duvvuri, Alexander Dimitrios Colevas, Jelena Levi, Nikita Bedi, Serena Chang, , James Zou

7-UP generates in silico 40-plex CODEX data from a 7-plex mIF panel using cellular morphology, enabling cell type classification and survival prediction across diverse samples.

PNAS Nexus · May 19, 2023Peer-reviewedBioinformatics

SPACE-GM: geometric deep learning of disease-associated microenvironments from multiplex spatial protein profiles.

Zhenqin Wu, Alexandro E. Trevino, Eric Wu, Kyle Swanson, Honesty Kim, H. Blaize D’Angio, Ryan Preska, Gregory W. Charville, Piero D. Dalerba, Ann Marie Egloff, Ravindra Uppaluri, Umamaheswar Duvvuri, Aaron T. Mayer, James Zou

SPACE-GM identifies spatial motifs in cancer samples linked to recurrence and immunotherapy outcomes using geometric deep learning.

Nature Biomedical Engineering · Nov 10, 2022Peer-reviewedBioinformatics