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Power grids to epidemics: study shows small patterns trigger systemic failures

Researchers identified small clusters of interacting components that act as amplifiers, triggering outsized reactions in complex systems. These clusters can control how strongly a system reacts after a disruption, and their presence can determine the stability of entire systems.

SourceFlorida Atlantic University·JournalProceedings of the National Academy of Sciences·TypeComputational simulation/modeling·DateFeb 18, 2026

UVA professor tackles graph mining challenges with new algorithm

A UVA professor has developed a new computational algorithm to find tightly connected clusters, or triangle-dense subgraphs, within large networks. This breakthrough can help uncover suspicious activity in fraud detection and identify community dynamics on social media with greater precision.

SourceUniversity of Virginia School of Engineering and Applied Science·JournalIEEE Transactions on Knowledge and Data Engineering·TypeComputational simulation/modeling·DateOct 18, 2024

Unraveling biological networks

Researchers develop efficient algorithm to detect recurring patterns of interconnections in biological networks, shedding light on cellular processes and disease mechanisms. The approach has revealed novel motifs previously unrecognized, offering new insights into complex networks.

SourceInderscience Publishers·JournalInternational Journal of Data Mining and Bioinformatics·DateMar 5, 2012
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Navigating an integrated yeast network

Lan Zhang et al. integrated five biological relationships to discover recurring patterns and themes, highlighting previously unknown relationships between functional modules. Their approach can predict interactions and gene functions, offering a basis for detailed network reconstruction and understanding biological networks.

SourceBMC (BioMed Central)·JournalJournal of Biology·DateMay 31, 2005

Genes, neurons, and the Internet found to have some identical organizing principles

Researchers discovered identical organizing principles in genetic, neural, and food networks, revealing potential strategies for information processing and filtering noise. The study's findings have significant implications for understanding complex systems and could lead to breakthroughs in fields like medicine and electronics.

SourceAmerican Committee for the Weizmann Institute of Science·JournalScience·DateNov 6, 2002