Author

Jayashabari Shankar

MIT Computer Science and Artificial Intelligence Laboratory

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Genomics· 1

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Assay:ChIP-seq· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Bessie Li· 1 shared Dimitar Ivanov· 1 shared Janet H. T. SongiD· 1 shared Krish Vasudev· 1 shared M KellisiD· 1 shared Martin WohlwendiD· 1 shared Nikitha ThoduguliiD· 1 shared Riley J. ManganiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperGenomics

Bessie Li

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1 paper

Recent·Most cited

Sequence-to-function deep learning decodes human cis-regulatory evolution

Riley J. Mangan, Nikitha Thoduguli, Dimitar Ivanov, Bessie Li, Krish Vasudev, Tom Zeerow, Jayashabari Shankar, Yuru Lin, Zunpeng Liu, Martin Wohlwend, Janet H. T. Song, M Kellis

This study uses sequence-to-function deep learning to identify lineage-specific cis-regulatory elements in human evolution, finding they are shorter, less conserved, and enriched in neurodevelopmental pathways.

bioRxiv · Aug 27, 2026 · PreprintGenomics