A roadmap of clustering algorithms: finding a match for a biomedical application

@article{Andreopoulos2009ARO,
  title={A roadmap of clustering algorithms: finding a match for a biomedical application},
  author={Bill Andreopoulos and Aijun An and Xiaogang Wang and Michael Schroeder},
  journal={Briefings in bioinformatics},
  year={2009},
  volume={10 3},
  pages={297-314}
}
Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable… CONTINUE READING
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