Author

Vega Shah

Nvidia (United States)

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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Neuroscience· 1

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Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:scRNA-seq· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Anna Rychkova· 1 shared Birkan GökbağiD· 1 shared Isabel V. L. WilkinsoniD· 1 shared Jens Christian SchwamborniD· 1 shared John St John· 1 shared Jun Yin· 1 shared Maya L. GosztylaiD· 1 shared Robert T. Fremeau· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 36 mutual co-author links

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1 shared paperNeuroscience

Anna Rychkova

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1 paper

Recent·Most cited

Interpretable gene networks from single-cell foundation models reveal conserved neurogenic dysfunction in Parkinson's disease

Jun Yin, Maya L. Gosztyla, Birkan Gökbağ, Anna Rychkova, Isabel V. L. Wilkinson, John St John, Vega Shah, Sarah Nickels, Jens Christian Schwamborn, Robert T. Fremeau

The paper introduces scGENet, a framework to generate interpretable gene networks from single-cell foundation models, revealing conserved neurogenic dysfunction in Parkinson's disease.

bioRxiv · Jul 27, 2026 · PreprintNeuroscience