Author

Deep Ray

University of Maryland, College ParkORCID 0000-0002-8460-9862Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Approach:deep learning· 2 Organism:human· 2 Research Focus:trajectory inference· 2 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:statistical model· 1

Frequent Co-Authors

Saumyadipta PyneiD· 2 shared Meghana Ray· 1 shared Meghana S. Ray· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

3 top collaborators · 2 mutual co-author links

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2 shared papersBioinformatics

Saumyadipta PyneORCID

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2 papers

Recent·Most cited

BioinformaticsFrontiers in AgingPeer-reviewedJul 15, 2026

Automated generation of personalized trajectories of aging phenotypes with DyViA-GAN

Saumyadipta Pyne, Deep Ray, Meghana S. Ray

The paper develops DyViA-GAN to predict personalized aging phenotype trajectories using longitudinal data, showing its potential in healthspan research.

DOI 10.3389/fragi.2026.1724246

humanbulk RNA-seq

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BioinformaticsbioRxivPreprintJul 9, 2026

Generative AI Models Reveal Dynamic Views of Aging (DyViA) Phenotypes in Healthy Individuals

Deep Ray, Meghana Ray, Saumyadipta Pyne

DyViA uses generative AI to create personalized aging trajectory models for femoral neck BMD, showing dynamic progression from 66 to 89 years.

DOI 10.64898/2026.07.05.735302

humanbulk RNA-seq

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