Author

Jodi Lee

Gladstone Institutes

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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Genomics· 2

Signature Assays, Organisms & Methods

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Assay:ATAC-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:long-read sequencing· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

Katherine S. PollardiD· 2 shared Benoit G. BruneauiD· 1 shared Daniel QuiatiD· 1 shared Ethan Shurberg· 1 shared Geoffrey FudenbergiD· 1 shared Jingshing Wu· 1 shared Kaite ZhangiD· 1 shared Kelly Hayes· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersGenomics

Katherine S. PollardORCID

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2 papers

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

Structural variants in human congenital heart disease disrupt distal genomic regulatory contacts of developmental genes

Jodi Lee, Jingshing Wu, Maureen Pittman, Zoe L. Grant, Shuzhen Kuang, Daniel Quiat, Sarah U. Morton, Geoffrey Fudenberg, Michela Traglia, Kelly Hayes, Ritu Kumar, Benoit G. Bruneau, Katherine S. Pollard

The paper develops a machine-learning model to predict how structural variants disrupt 3D chromatin structure in congenital heart disease and validates its predictions using induced pluripotent stem cells.

bioRxiv · Mar 2, 2026 · PreprintGenomics