ArticleNature communications2022
Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Metabolic reprogramming of myeloid cells in cancer: from lactate-NAMPT axis to AI-guided therapeutics.Experimental & molecular medicine · 2026Review
- BioMedGraphica: an all-in-one platform for joint textual biomedical prior knowledge and numeric graph generation.Bioinformatics (Oxford, England) · 2026Article
- Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Phenotypic AI-based design of cell-specific small molecule cytotoxics.Communications chemistry · 2026Article
- SCONE: a subset-contrastive method for multi-omics network embedding.Briefings in bioinformatics · 2026Article
- CellAwareGNN: Single-Cell Enhanced Knowledge Graph Foundation Model for Drug Indication Prediction.bioRxiv : the preprint server for biology · 2026Article
- Integrating explainable artificial intelligence with multiomics systems biology and electronic health record data mining for personalized drug repurposing in Alzheimer's disease.Briefings in bioinformatics · 2025Article
- Artificial intelligence coupled to pharmacometrics modelling to tailor malaria and tuberculosis treatment in Africa.Nature communications · 2025Article
- BioMedGraphica: An All-in-One Platform for Joint Textual Biomedical Prior Knowledge and Numeric Graph Generation.bioRxiv : the preprint server for biology · 2025Article
- Article
- A Multi-Layered Framework for Modeling Human Biology: From Basic AI Agents to a Full-Body AI Agent.ArXiv · 2025Article
- Integrating explainable AI with multiomics systems biology and EHR data mining for personalized drug repurposing in Alzheimer's disease.bioRxiv : the preprint server for biology · 2025Article
- Computational drug repurposing: approaches, evaluation of in silico resources and case studies.Nature reviews. Drug discovery · 2025Review
- medicX-KG: a knowledge graph for pharmacists' drug information needs.Journal of biomedical semantics · 2025Article
- A Knowledge-Guided Graph Learning Approach Bridging Phenotype- and Target-Based Drug Discovery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Unsupervised cell line embedding using pairwise drug response correlation.Computational and structural biotechnology journal · 2025Article
- A spatial hierarchical network learning framework for drug repositioning allowing interpretation from macro to micro scale.Communications biology · 2024Article
- Knowledge Graphs for drug repurposing: a review of databases and methods.Briefings in bioinformatics · 2024Review
- Comprehensive detection and characterization of human druggable pockets through binding site descriptors.Nature communications · 2024Article
- Graph Artificial Intelligence in Medicine.Annual review of biomedical data science · 2024Review
Corrections and comments
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5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biomedical data is accumulating at a fast pace and integrating it into a unified framework is a major challenge, so that multiple views of a given biological event can be considered simultaneously. Here we present the Bioteque, a resource of unprecedented size and scope that contains pre-calculated biomedical descriptors derived from a gigantic knowledge graph, displaying more than 450 thousand biological entities and 30 million relationships between them. The Bioteque integrates, harmonizes, and formats data collected from over 150 data sources, including 12 biological entities (e.g., genes, diseases, drugs) linked by 67 types of associations (e.g., 'drug treats disease', 'gene interacts with gene'). We show how Bioteque descriptors facilitate the assessment of high-throughput protein-protein interactome data, the prediction of drug response and new repurposing opportunities, and demonstrate that they can be used off-the-shelf in downstream machine learning tasks without loss of performance with respect to using original data. The Bioteque thus offers a thoroughly processed, tractable, and highly optimized assembly of the biomedical knowledge available in the public domain.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.