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Benefit Ledger · provisional · Other

Structured cross-omics interaction discovery with a triple-graph model

Multi-omics analyses often yield fragmented pairwise associations that obscure coordinated relationships among molecular features. We developed TriGer, a triple-graph framework that identifies many-to-many cross-omics modules by combining cross-layer associations with dependency structures within each layer. In simulations with sparse or nested signals, TriGer recovered planted modules while balancing sensitivity and specificity. In inflammatory bowel disease, it identified subtype-associated metabolite--transcript modules; in colorectal cancer, it identified genus--metabolite modules whose or

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Current score

+0.05

1 base · Useful (tier 1 of 5, 1 pts)
× 0.7500 attribution · Critical contribution
× 0.3500 evidence · Technical disclosure or preprint
× 0.4000 realization · Demonstrated
× 0.5000 durability · Medium-term
Event-level product before credit split: 0.05

Ingest update: raised attribution; raised evidence; raised realization. Score remains provisional until review.

What happened

Multi-omics analyses often yield fragmented pairwise associations that obscure coordinated relationships among molecular features. We developed TriGer, a triple-graph framework that identifies many-to-many cross-omics modules by combining cross-layer associations with dependency structures within each layer. In simulations with sparse or nested signals, TriGer recovered planted modules while balancing sensitivity and specificity. In inflammatory bowel disease, it identified subtype-associated metabolite--transcript modules; in colorectal cancer, it identified genus--metabolite modules whose organization was attenuated in cancer. TriGer provides an interpretable approach for studying coordinated cross-omics structure in high-dimensional molecular data. Update (2026-09-16): Structured cross-omics interaction discovery with a triple-graph model . Multi-omics analyses often yield fragmented pairwise associations that obscure coordinated relationships among molecular features. We developed TriGer, a triple-graph framework that identifies many-to-many cross-omics modules by combining cross-layer associations with dependency structures within each layer. In simulations with sparse or nested signals, TriGer recovered planted modules while balancing sensitivity and specificity. In inflammatory bowel disease, it identified subtype-associated metabolite--transcript modules; in colorectal cancer, it identified genus--metabolite modules whose organization was attenuated in cancer. TriGer provides an interpretable approach for studying coordinated cross-omics structure in high-dimensional molecular data.

Model attribution

Unspecified AI system
Version unspecified
+0.05

Unspecified

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Attribution 0.7500 · Credit share 100% · Unknown

Claims

  • Structured cross-omics interaction discovery with a triple-graph model

    outcome · supported

Sources

primary sources

Revision history

  • 16 Sep 2026 · 0.00 → 0.00

    Auto-published from news ingest.

  • 17 Sep 2026 · 0.00 → 0.05

    Ingest update: raised attribution; raised evidence; raised realization.