ArticleBMC systems biology2013
Interaction network among functional drug groups.
Article in BMC systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- MD-Syn: synergistic drug combination prediction based on a multidimensional feature fusion method and attention mechanisms.Frontiers in pharmacology · 2025Article
- A two-tiered unsupervised clustering approach for drug repositioning through heterogeneous data integration.BMC bioinformatics · 2018Article
- OWL-NETS: Transforming OWL Representations for Improved Network Inference.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- InCoB2013 introduces Systems Biology as a major conference theme.BMC systems biology · 2013Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMore attention has been being paid to combinatorial effects of drugs to treat complex diseases or to avoid adverse combinations of drug cocktail. Although drug interaction information has been increasingly accumulated, a novel approach like network-based method is needed to analyse that information systematically and intuitively
resultsBeyond focussing on drug-drug interactions, we examined interactions between functional drug groups. In this work, functional drug groups were defined based on the Anatomical Therapeutic Chemical (ATC) Classification System. We defined criteria whether two functional drug groups are related. Then we constructed the interaction network of drug groups. The resulting network provides intuitive interpretations. We further constructed another network based on interaction sharing ratio of the first network. Subsequent analysis of the networks showed that some features of drugs can be well described by this kind of interaction even for the case of structurally dissimilar drugs.
conclusionOur networks in this work provide intuitive insights into interactions among drug groups rather than those among single drugs. In addition, information on these interactions can be used as a useful source to describe mechanisms and features of drugs.
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