Author

Vijay S. Ramani

Gladstone Institutes

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Genomics· 1

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Assay:ATAC-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:long-read sequencing· 1 Organism:mouse· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Ethan Shurberg· 1 shared Jodi Lee· 1 shared Kaite ZhangiD· 1 shared Katherine S. PollardiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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4 top collaborators · 6 mutual co-author links

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1 shared paperGenomics

Ethan Shurberg

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1 paper

Recent·Most cited

ChAI-Net learns a regulatory code for chromatin co-accessibility

Jodi Lee, Kaite Zhang, Ethan Shurberg, Vijay S. Ramani, Katherine S. Pollard

The paper introduces ChAI-Net, a deep learning model that predicts chromatin co-accessibility from DNA sequences in mouse embryonic stem cells, revealing sequence motifs that govern coordinated TF binding.

bioRxiv · Oct 31, 2026 · PreprintGenomics