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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Identifying Phytochemicals from Biomedical Literature Utilizing Semantic Knowledge Sources.

Indra Neil Sarkar1, Wayne Law2, Michael J Balick2

  • 1Center for Biomedical Informatics, Brown University, Providence, RI, USA.

Studies in Health Technology and Informatics
|August 24, 2019
PubMed
Summary

This study explored using semantic knowledge sources to identify plant phytochemicals, finding this approach can help catalog medicinal plant compounds. While promising, current electronic data shows gaps compared to established databases.

Keywords:
Knowledge BasesMedicinalPhytochemicalsPlants

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Area of Science:

  • Pharmacognosy
  • Bioinformatics
  • Cheminformatics

Background:

  • Phytochemicals, or plant-derived chemicals, are crucial in medicinal plant research.
  • Current phytochemical knowledge cataloging relies heavily on manual methods.
  • There is a need for automated and scalable approaches to manage phytochemical data.

Purpose of the Study:

  • To investigate the feasibility of using public semantic knowledge sources for phytochemical identification.
  • To develop and test a method for extracting potential phytochemicals from biomedical databases.
  • To assess the completeness of electronically cataloged phytochemical information.

Main Methods:

  • Utilized Medical Subject Headings Supplementary Concept Records and Semantic MEDLINE Database.
  • Applied a novel method to identify putative phytochemicals for over 4,000 plant species.
  • Compared identified phytochemicals against Dr. Duke's Phytochemical and Ethnobotanical Databases for validation.

Main Results:

  • Successfully identified potential phytochemicals for a large number of plants using semantic sources.
  • Revealed a notable disparity between electronically cataloged phytochemical data and established databases for selected species.
  • Demonstrated the potential of semantic knowledge sources in uncovering phytochemical information.

Conclusions:

  • Publicly accessible semantic knowledge sources are a viable resource for identifying potential phytochemicals.
  • This approach can significantly aid in the curation and expansion of plant phytochemical knowledge.
  • Further development is needed to reconcile disparities and enhance data completeness.