| Literature DB >> 27818847 |
Nathan Alexander1, Nils Woetzel1, Jens Meiler1.
Abstract
Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.Entities:
Keywords: Pymol; analysis; clustering; molecules; proteins; visualization
Year: 2011 PMID: 27818847 PMCID: PMC5091839 DOI: 10.1109/ICCABS.2011.5729867
Source DB: PubMed Journal: IEEE Int Conf Comput Adv Bio Med Sci ISSN: 2164-229X