# Multi-modal Protein Knowledge Graph Construction and Applications

arXiv: https://arxiv.org/abs/2207.10080 · HTML: https://mlsanity.com/paper/2207.10080/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 2 references that are in the map.
- First posted on arXiv 27 May 2022.

## Built on by (most cited first, 2 of 2)

- [Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications](https://mlsanity.com/paper/2501.11632/) (2025)
- [AgentPLM: Agentic Protein Language Models with Reasoning-Augmented Decoding for Protein Sequence Design](https://mlsanity.com/paper/2606.02386/) (2026)

## Abstract (arXiv)

Existing data-centric methods for protein science generally cannot sufficiently capture and leverage biology knowledge, which may be crucial for many protein tasks. To facilitate research in this field, we create ProteinKG65, a knowledge graph for protein science. Using gene ontology and Uniprot knowledge base as a basis, we transform and integrate various kinds of knowledge with aligned descriptions and protein sequences, respectively, to GO terms and protein entities. ProteinKG65 is mainly dedicated to providing a specialized protein knowledge graph, bringing the knowledge of Gene Ontology to protein function and structure prediction. We also illustrate the potential applications of ProteinKG65 with a prototype. Our dataset can be downloaded at https://w3id.org/proteinkg65.