Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network

Lee, Namgil; Yoo, Hojin; Yang, Heejung

doi:10.1101/2020.04.20.050021

Cited by 1 publication

(2 citation statements)

References 54 publications

(21 reference statements)

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“…Network tools give functionality for studying complex processes. We can analyze the global characteristics of the data via metrics such as degree, clustering, shortest path, centrality, and density, [19]. We can identify key elements, and important subnets which could help us explore interaction mechanisms, modularity, etc.…”

Section: Biological Network Analysismentioning

confidence: 99%

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Biomolecular Network-based Study of a Parasitic Disease and Therapeutic Drugs

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Erdenedalai

Erdenechimeg³

et al. 2022

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Computational drug repurposing methods, particularly biomolecular network-based disease-drug-target interaction models, are essential tools for integrating large-scale heterogenous molecular information and revealing functional mechanisms, as well as for main regulatory modules of interactants which can be useful in developing new drugs. In the present study, a drug-centric network for a parasitic disease (Echinococcosis) and therapeutic drugs have been considered. A complex network with more than 12,000 vertices and more than 33,000 edges representing interactions of 84 echinococcosis-related genes with associated proteins was built and analyzed. The networks of disease similarity and drug similarity were constructed based on the complex network. As a result, three drugs (D08356, D00701, and D00506) associated with three candidate diseases through three pathways and a protein complex have been extracted. This effort tries to predict the anti-echinococcosis effects of the drugs’ combinations with benzimidazole.

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Section: Biological Network Analysismentioning

confidence: 99%

“…Clustering methods are commonly used in biological network analysis to group network elements based on certain metrics, [19]. A variety of algorithms are used for cluster analysis, all based on the similarity measure of elements.…”

Section: Biological Network Analysismentioning

confidence: 99%