Data-Driven Discovery of Regulatory Mechanisms and Cellular Resource Allocation via Multi-Modal Data Integration

Integrates multi-omics data from single-cell sequencing across well-characterized model cell lines. Creates a benchmarking resource for understanding regulatory mechanisms and cellular adaptation across molecular layers.

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Author Elizabeth Brunk
Last Updated September 10, 2026, 18:10 (UTC)
Published August 5, 2026, 18:11 (UTC)
Citation Elizabeth Brunk 2025. Data-Driven Discovery of Regulatory Mechanisms and Cellular Resource Allocation via Multi-Modal Data Integration. CyVerse Data Commons.
Description Integrates multi-omics data from single-cell sequencing across well-characterized model cell lines. Creates a benchmarking resource for understanding regulatory mechanisms and cellular adaptation across molecular layers.
PublicationYear 2025
Publisher CyVerse Data Commons
Rights This material is based upon work supported by the U.S. National Science Foundation under Award No. #2335029. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation.
Subject multi-omics integration, gene regulation, cellular responses, cell line benchmarking, network biology, single-cell sequencing
de_created_date 2026-03-04T17:23:01Z
de_modified_date 2026-07-28T22:07:47Z