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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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L'apport de la théorie des graphes à l'ethnopharmacologie : une modélisation systémique des usages des plantes et de leurs effets thérapeutiques

Authors: Aubert, Elora; Petitjean, Hugues;

L'apport de la théorie des graphes à l'ethnopharmacologie : une modélisation systémique des usages des plantes et de leurs effets thérapeutiques

Abstract

The contribution of graph theory to ethnopharmacology. Systemic modeling of plant uses and therapeutic effects Ethnopharmacology is the study of remedies and ingredients used in different traditional medicines in aim to identify new therapeutic solutions. These studies generally consist of identifying and isolating a new main active compound from one medicinal plant. However, several studies show a loss of biological activity between traditional use and isolated compounds, suggesting a more complex therapeutic mechanism. The systemic approach of network pharmacology, based on graph theory, makes possible the study of this theory with the in silico modeling of multiple possible interactions between plant compounds and human proteins. The in silico study of these complex networks can help to spot target and compounds essential to the observed therapeutic activity.

Keywords

Graph theory, Big data, Ethnopharmacology, Ethnobotany, Systems modeling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average