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datadrivenhypothesis.org: A resource for metabolic gene discovery through integrated pathway co-essentiality mapping

Year: 2026

Type: preprint

Abstract: datadrivenhypothesis.org (DDH) integrates gene dependency, expression, literature data, and beyond from ~20,000 human genes to reveal hidden metabolic connections. Through pathway-level co-essentiality analysis with novelty scoring, DDH uncovered unexpected links including Complex II coupled to purine nucleotide biosynthesis. This broad platform offers intuitive tools for hypothesis generation via gene queries, pathway analysis, and network visualization, plus publication-ready downloads. Automated updates make DDH a dynamic resource, bridging genes with unknown function to actionable metabolic insights.

Source: bioRxiv (Cold Spring Harbor Laboratory)

DOI: 10.64898/2026.02.11.705287

Authors: Matthew D. Hirschey, Pol Castellano-Escuder, John Bradley

Institutions: National University of Singapore, Duke University, Duke Medical Center, Duke-NUS Medical School

Language: English

Topic: Bioinformatics and Genomic Networks

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases

Awards: Studies on the Mechanisms by which SIRT5 Regulates Aging and Disease, Post-Translational and Epigenetic Control of Branched-Chain Amino Acid Metabolism, Cancer Center Support Grant (CCSG)

OpenAlex ID: W7128740514

Cites: 9

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