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Related Concept Videos

Taxonomy01:31

Taxonomy

Taxonomy is the science of defining and naming groups of biological organisms based on shared characteristics. It uses a hierarchy of increasingly inclusive categories with Latin names. The smallest units of taxonomy, species and genus, are used to assign a formal, taxonomic name to each species in a system. This classification system, referred to as binomial nomenclature, was formalized by Carolus Linnaeus in the 18th century.Hierarchy of TaxonomyThe hierarchy that Carolus Linnaeus first...
Enzyme-linked Receptors01:00

Enzyme-linked Receptors

Enzyme-linked receptors are proteins that act as both receptor and enzyme, activating multiple intracellular signals. This is a large group of receptors that include the receptor tyrosine kinase (RTK) family. Many growth factors and hormones bind to and activate the RTKs.
Neurotrophin (NT) receptors are a family of RTKs, including trkA, trkB, and trkC (tropomyosin-related kinase) receptors. TrkA is specific for nerve growth factor (NGF), neurotrophin-6, and neurotrophin-7. TrkB binds...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence the...

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Related Experiment Video

Updated: Jul 8, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

TaxEL: Taxonomy-Enhanced Entity Representation Learning for Biomedical Entity Linking.

Rui Hua, Zeyu Liu, Zixin Shu

    IEEE Journal of Biomedical and Health Informatics
    |July 6, 2026
    PubMed
    Summary

    Taxonomy-Enhanced Entity Linking (TaxEL) improves biomedical entity linking by using taxonomy structure for better candidate sampling and supervision. This novel framework achieves state-of-the-art results on multiple benchmarks.

    Related Experiment Videos

    Last Updated: Jul 8, 2026

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
    07:35

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

    Published on: October 13, 2023

    Area of Science:

    • Biomedical informatics
    • Natural Language Processing
    • Ontology Engineering

    Background:

    • Biomedical entity linking (BioEL) maps mentions to ontology concepts.
    • Existing methods often overlook the hierarchical structure of biomedical taxonomies.
    • This limitation restricts capturing nuanced semantic relationships and entity similarity.

    Purpose of the Study:

    • To propose a novel framework, Taxonomy-Enhanced Entity Linking (TaxEL), for improved BioEL.
    • To leverage the hierarchical structure of biomedical ontologies for more effective linking.
    • To enhance the ability of BioEL systems to capture semantic nuances and entity similarity.

    Main Methods:

    • TaxEL unifies taxonomy-guided candidate sampling and structure-aware distributional supervision.
    • Taxonomy-Guided Contrastive Sampling (TGCS) integrates local and global ontology structure for sample generation.
    • Structured Semantic Alignment Loss (SSAL) enforces alignment with taxonomy-derived semantic distributions.

    Main Results:

    • TaxEL achieved state-of-the-art performance in accuracy (Acc@1) across five public BioEL benchmarks.
    • Ablation studies confirmed the significant contributions of both TGCS and SSAL components.
    • The proposed methods demonstrate superior performance compared to existing BioEL approaches.

    Conclusions:

    • TaxEL offers a novel and effective approach to biomedical entity linking by incorporating taxonomic information.
    • The framework enhances the understanding of semantic relationships and entity similarity in biomedical text.
    • TaxEL provides a publicly accessible web service and open-source code for broader research use.