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Summary
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This study introduces textToKnowledgeGraph, an AI tool using Large Language Models (LLMs) to automatically extract biological interactions from text into Biological Expression Language (BEL), improving knowledge graph construction.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Artificial Intelligence in Biology

Background:

  • Knowledge graphs (KGs) are vital for biological data analysis but manual construction from literature is costly and time-consuming.
  • Existing text-mining methods struggle with contextual understanding and inferring complex biological relationships.
  • Large Language Models (LLMs) offer enhanced contextual knowledge for more accurate information extraction.

Purpose of the Study:

  • To develop an automated method for extracting biological interactions from scientific literature.
  • To represent extracted biological relationships in the structured Biological Expression Language (BEL).
  • To overcome limitations of traditional text-mining approaches in capturing complex biological context.

Main Methods:

  • Utilized Large Language Models (LLMs) to process scientific articles and extract biological interactions.
  • Developed the open-source Python package `textToKnowledgeGraph` for automated extraction.
  • Integrated an interactive application within Cytoscape Web for simplified extraction and exploration.

Main Results:

  • Successfully extracted biological interactions directly into Biological Expression Language (BEL) format.
  • Created an open-source tool and an interactive application for knowledge graph construction.
  • Generated a reviewed dataset of extractions to facilitate future model fine-tuning.

Conclusions:

  • The `textToKnowledgeGraph` tool enhances the automated construction of biological knowledge graphs.
  • LLM-powered extraction into BEL provides a structured and computationally accessible representation of biological relationships.
  • This work facilitates more efficient and accurate biological data analysis and knowledge discovery.