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Network AI Statistical Analysis Lab
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The lab statistically investigates networks using graph spectra.
AboutAbout the lab
Reading the structure of networks through statistics.
The Network AI Statistical Analysis Joint Research Division is a joint research division of the Medical Institute of Bioregulation.
A paper for which Prof. Fujita served as last author covers a method for efficiently examining large networks using graph spectra and a method for statistically examining directed networks.
The paper also introduces statGraph, an R package that bundles statistical analyses such as network comparison and clustering.
Prof. Fujita is also a coauthor of a paper that examined brain functional connectivity and gene expression data using network concepts.
Key terms
- Graph spectrum
- The set of eigenvalues of the matrix representing a network. It carries information about the network's structure and serves as a basis for statistical inference.
- statGraph
- An R package for statistical analysis of networks, including comparison, clustering, and model selection.
ResearchResearch themes
In the researcher profile of this lab's professor, network statistics, human behavior, graph spectra, computational statistics, and complex networks are listed as research topics. The papers cover a method that uses graph spectra to statistically investigate how networks are generated, which cannot be observed directly.
View More ↗MembersFaculty
- ProfessorAndre Fujita
- Assistant ProfessorPatricia Severino
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Airports Network Map” Martin Grandjean / CC BY-SA 4.0 (cropped)
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