ArticleBioinformatics (Oxford, England)2011
Interactive, multiscale navigation of large and complicated biological networks.
Article in Bioinformatics (Oxford, England), 2011. 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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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
4 citing papers in PubMed.
- Modularity in Biological Networks.Frontiers in genetics · 2021Review
- COXPRESdb: a database of comparative gene coexpression networks of eleven species for mammals.Nucleic acids research · 2013Article
- A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.BioData mining · 2012Article
- Integration of interactive, multi-scale network navigation approach with Cytoscape for functional genomics in the big data era.BMC genomics · 2012Article
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Authors and funding
3 authors.
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Abstract
motivationMany types of omics data are compiled as lists of connections between elements and visualized as networks or graphs where the nodes and edges correspond to the elements and the connections, respectively. However, these networks often appear as 'hair-balls'-with a large number of extremely tangled edges-and cannot be visually interpreted.
resultsWe present an interactive, multiscale navigation method for biological networks. Our approach can automatically and rapidly abstract any portion of a large network of interest to an immediately interpretable extent. The method is based on an ultrafast graph clustering technique that abstracts networks of about 100 000 nodes in a second by iteratively grouping densely connected portions and a biological-property-based clustering technique that takes advantage of biological information often provided for biological entities (e.g. Gene Ontology terms). It was confirmed to be effective by applying it to real yeast protein network data, and would greatly help modern biologists faced with large, complicated networks in a similar manner to how Web mapping services enable interactive multiscale navigation of geographical maps (e.g. Google Maps). AVAILABILITY: Java implementation of our method, named NaviCluster, is available at http://navicluster.cb.k.u-tokyo.ac.jp/. CONTACT: thanet@cb.k.u-tokyo.ac.jp SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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