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Gütlein M, Karwath A, Kramer S. CheS-Mapper - Chemical Space Mapping and Visualization in 3D. J Cheminform. 2012;4(1):7doi: 10.1186/1758-2946-4-7.
Gütlein, M., Karwath, A., & Kramer, S. (2012). CheS-Mapper - Chemical Space Mapping and Visualization in 3D. Journal of cheminformatics, 4(1), 7. https://doi.org/10.1186/1758-2946-4-7
Gütlein, Martin, et al. "CheS-Mapper - Chemical Space Mapping and Visualization in 3D." Journal of cheminformatics vol. 4,1 (2012): 7. doi: https://doi.org/10.1186/1758-2946-4-7
Gütlein M, Karwath A, Kramer S. CheS-Mapper - Chemical Space Mapping and Visualization in 3D. J Cheminform. 2012 Mar 17;4(1):7. doi: 10.1186/1758-2946-4-7. PMID: 22424447; PMCID: PMC3331825.
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J Cheminform. 2012 Mar 17;4(1):7. doi: 10.1186/1758-2946-4-7.

CheS-Mapper - Chemical Space Mapping and Visualization in 3D.

Journal of cheminformatics

Martin Gütlein, Andreas Karwath, Stefan Kramer

Affiliations

  1. Department of Computer Science, Albert-Ludwigs-Universität Freiburg, Freiburg im Breisgau, Germany. [email protected].

PMID: 22424447 PMCID: PMC3331825 DOI: 10.1186/1758-2946-4-7

Abstract

Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kind of features, like structural fragments as well as quantitative chemical descriptors. These features can be highlighted within CheS-Mapper, which aids the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. As a final function, the tool can also be used to select and export specific subsets of a given dataset for further analysis.

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