ArticlePloS one2019
Clustering of the structures by using "snakes-&-dragons" approach, or correlation matrix as a signal.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- An Inflammatory Composite Score Predicts Mycobacterial Immune Reconstitution Inflammatory Syndrome in People with Advanced HIV: A Prospective International Cohort Study.The Journal of infectious diseases · 2021Observational
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Authors and funding
6 authors.
Funding
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Abstract
Biological, ecological, social, and technological systems are complex structures with multiple interacting parts, often represented by networks. Correlation matrices describing interdependency of the variables in such structures provide key information for comparison and classification of such systems. Classification based on correlation matrices could supplement or improve classification based on variable values, since the former reveals similarities in system structures, while the latter relies on the similarities in system states. Importantly, this approach of clustering correlation matrices is different from clustering elements of the correlation matrices, because our goal is to compare and cluster multiple networks-not the nodes within the networks. A novel approach for clustering correlation matrices, named "snakes-&-dragons," is introduced and illustrated by examples from neuroscience, human microbiome, and macroeconomics.
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