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OptimusKG: New multimodal biomedical graph unifies diverse life science data

Researchers have developed OptimusKG, a novel multimodal knowledge graph designed to unify diverse biomedical data. This graph integrates structured and semi-structured resources, encompassing molecular, anatomical, clinical, and environmental information. OptimusKG contains over 190,000 nodes and 21 million edges, preserving detailed metadata and provenance. Its validity was assessed using the PaperQA3 agent, which confirmed literature support for a significant portion of the graph's relationships. AI

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IMPACT Provides a standardized resource for graph-based machine learning and knowledge-grounded retrieval with large language models.

RANK_REASON This is a research paper describing a new biomedical knowledge graph.

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Lucas Vittor, Ayush Noori, I\~naki Arango, Joaqu\'in Polonuer, Sam Rodriques, Andrew White, David A. Clifton, Marinka Zitnik ·

    OptimusKG: Unifying biomedical knowledge in a modern multimodal graph

    arXiv:2604.27269v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) are widely used in the life sciences, yet many are derived from unstructured documents and therefore lack schema-level constrains, whereas graphs assembled from structured resources are difficult to…