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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
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such that their spatial proximity reflects their
similarity. The user can indirectly determine
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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
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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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|