On the Potential of Artificial Intelligence Chatbots for Data Exploration of Federated Bioinformatics Knowledge Graphs

Ana-Claudia Sima; Tarcisio Mendes de Farias

On the Potential of Artificial Intelligence Chatbots for Data Exploration of Federated Bioinformatics Knowledge Graphs

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arxiv 2304.10427 v1 pith:RXXEPG2C submitted 2023-04-20 cs.AI

Ana-Claudia Sima , Tarcisio Mendes de Farias This is my paper

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keywords federatedartificialbioinformaticschatbotsdatadatasetsgraphsintelligence

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In this paper, we present work in progress on the role of artificial intelligence (AI) chatbots, such as ChatGPT, in facilitating data access to federated knowledge graphs. In particular, we provide examples from the field of bioinformatics, to illustrate the potential use of Conversational AI to describe datasets, as well as generate and explain (federated) queries across datasets for the benefit of domain experts.

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MetaboT: An LLM-based Multi-Agent Frameworkfor Interactive Analysis of Mass SpectrometryMetabolomics Knowledge Graphs
cs.AI 2025-10 conditional novelty 6.0 of 10

A multi-agent LLM system converts natural-language metabolomics questions into SPARQL queries over the ENPKG knowledge graph, reaching 83.67% accuracy with GPT-4o versus 8.16% for the standalone model.

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