Cluster analysis is one of the most popular methods for the analysis of multi-parameter data. The cluster analysis reveals the internal structure of the data, group the separate observations on the degree of their similarity. The review provides a definition of the basic concepts of cluster analysis, and discusses the most popular clustering algorithms: k-means, hierarchical algorithms, Kohonen networks algorithms. Examples are the use of these algorithms in biomedical research.
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Harmful algal blooms are a critical eco-environmental issue with severe impacts on aquatic ecosystems and human health. Tannic acid (TA) has been suggested as an effective algal bloom control, but the molecular mechanisms of its interaction with algae cells and its effects on algal toxin release remain unclear. This study tracked toxin production and release in the toxigenic species Microcystis aeruginosa (M.
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Department of Psychology, University of Regensburg, Regensburg, Germany.
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