Pith Number

pith:GUMD27NW

pith:2026:GUMD27NWB4SOQ43GDQXV3PVUZ6

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Graph Neural Network based Hierarchy-Aware Embeddings of Knowledge Graphs: Applications to Yeast Phenotype Prediction

Alexander H. Gower, Daniel Brunns{\aa}ker, Filip Kronstr\"om, Ievgeniia A. Tiukova, Ross D. King

Graph neural networks enriched with semantic loss produce hierarchy-aware embeddings of yeast knowledge graphs that predict cell growth phenotypes from gene knockouts.

arxiv:2605.03690 v2 · 2026-05-05 · cs.LG · cs.AI · q-bio.QM

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Claims

C1strongest claim

Over 10-fold cross validation, these predictions have a mean R² score of 0.360, significantly higher than baseline comparisons... Incorporating semantic loss terms in the training of the models improves their predictive performance (R²=0.377) by aligning embeddings with ontology structure.

C2weakest assumption

That the yeast knowledge graph constructed from community databases and ontology terms contains the biologically relevant relationships needed to predict cell-growth phenotypes, and that the semantic loss term correctly enforces hierarchy without introducing new biases or data leakage.

C3one line summary

GNNs with ontology-derived semantic loss create hierarchy-aware KG embeddings that predict yeast double gene knockout phenotypes with mean R²=0.360 (improved to 0.377 with semantic loss), outperforming baselines, generalizing to triple knockouts, and supporting experimental hypothesis validation.

Receipt and verification

First computed	2026-05-21T02:05:03.888277Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

35183d7db60f24e873661c2f5dbeb4cf97004623978a8db34e5e9bb42a50aee9

Aliases

arxiv: 2605.03690 · arxiv_version: 2605.03690v2 · doi: 10.48550/arxiv.2605.03690 · pith_short_12: GUMD27NWB4SO · pith_short_16: GUMD27NWB4SOQ43G · pith_short_8: GUMD27NW

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GUMD27NWB4SOQ43GDQXV3PVUZ6 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 35183d7db60f24e873661c2f5dbeb4cf97004623978a8db34e5e9bb42a50aee9

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "ddaaf7316591cd842e042a7696e886b089bae987d79678d3139c19be5aa5ebf7",
    "cross_cats_sorted": [
      "cs.AI",
      "q-bio.QM"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-05T12:34:45Z",
    "title_canon_sha256": "da590924b7f95036a43a1b252a5ce1f1c08c54665566fbeb78145d272bb03369"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.03690",
    "kind": "arxiv",
    "version": 2
  }
}