An encyclopedia of human enhancer–gene regulatory interactions
Andreas R. Gschwind; Kristy S. Mualim; Alireza Karbalayghareh; Maya U. Sheth; Kushal K. Dey; Evelyn Jagoda; Ramil Nurtdinov; Wang Xi · 2026 · Nature
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the effect of human genetic variation on disease 1–6 . Here we create and evaluate a resource of more than 92 million enhancer–gene regulatory interactions across 1,458 biosamples covering 369 cell types and tissues, by integrating predictive models, chromatin states, three-dimensional contacts and large-scale genetic perturbations generated by the ENCODE Consortium 7 . We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 1
Abstract by Andreas R. Gschwind; Kristy S. Mualim; Alireza Karbalayghareh; Maya U. Sheth; Kushal K. Dey; Evelyn Jagoda; Ramil Nurtdinov; Wang Xi, Nature (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1038/s41586-026-10781-4