ArticleTheory in biosciences = Theorie in den Biowissenschaften2020
Edge-based analysis of networks: curvatures of graphs and hypergraphs.
Article in Theory in biosciences = Theorie in den Biowissenschaften, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Spaces of mathematical chemistry.Theory in biosciences = Theorie in den Biowissenschaften · 2024Article
- Molecular Mechanism Analysis of Intensive Light-Induced Retinal Damages.Journal of lasers in medical sciences · 2024Article
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Authors and funding
5 authors.
Funding
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Abstract
The relations, rather than the elements, constitute the structure of networks. We therefore develop a systematic approach to the analysis of networks, modelled as graphs or hypergraphs, that is based on structural properties of (hyper)edges, instead of vertices. For that purpose, we utilize so-called network curvatures. These curvatures quantify the local structural properties of (hyper)edges, that is, how, and how well, they are connected to others. In the case of directed networks, they assess the input they receive and the output they produce, and relations between them. With those tools, we can investigate biological networks. As examples, we apply our methods here to protein-protein interaction, transcriptional regulatory and metabolic networks.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.