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Soft X-ray spectromicroscopy provides spectral data on the chemical speciation of light elements at sub-100 nm spatial resolution. When all chemical species in a specimen are known and separately characterized, existing approaches can be used to measure the concentration of each component at each pixel. In other cases (such as often occur in biology or(More)
Sequential agglomerative hierarchical non-overlapping (SAHN) clustering techniques [10] belong to the classical clustering methods that are applied heavily in many application domains, e.g., in cheminformatics [4]. Asymptotically optimal SAHN clustering algorithms are known for arbitrary dissimilarity measures, but their quadratic time and space complexity(More)
The growing interest in chemogenomics approaches over the last years has led to a vast amount of data regarding chemical and the corresponding biological activity space. The discovery of new chemical entities is not suitable to a fully automated analysis, but can greatly benefit from tools that allow exploring this chemical and biological space. We present(More)
Sequential agglomerative hierarchical non-overlapping (SAHN) clustering techniques belong to the classical clustering methods applied heavily in many application domains, e.g., in cheminformatics. Asymptotically optimal SAHN clustering algorithms are known for arbitrary dissimilarity measures, but their quadratic time and space complexity even in the best(More)
—We present a structural clustering algorithm for large-scale datasets of small labeled graphs, utilizing a frequent subgraph sampling strategy. A set of representatives provides an intuitive description of each cluster, supports the clustering process, and helps to interpret the clustering results. The projection-based nature of the clustering approach(More)
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