Introducing fuzziness into maximum common substructures for meaningful cluster characterisation
نویسندگان
چکیده
منابع مشابه
Introducing fuzziness into maximum common substructures for meaningful cluster characterisation
Arranging similar structures in clusters is one of the typical tasks of modern Chemoinformatics with high impact in HTS follow-up, generation of structure activity relationships (SAR) and selection of starting points for compound optimisation. Methods for cluster generation are as diverse as the structures which they are applied to [1], may they be e.g. similarityor substructure-based. Typicall...
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Information about the unknown chemical structure of an organic compound can be obtained by comparing the infrared spectrum with the spectra of a spectral library. The resulting hitlist contains compounds exhibiting the most similar spectra. A method based on the maximum common substructure concept has been developed for an automatic extraction of common structural features from the hitlist stru...
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The abundance and structure of dark matter subhalos has been analyzed extensively in recent studies of dark matter-only simulations, but comparatively little is known about the impact of baryonic physics on halo substructures. We here extend the SUBFIND algorithm for substructure identification such that it can be reliably applied to dissipative hydrodynamical simulations that include star form...
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Imperfection in information can be considered a cross–cutting concern that manifests itself in diverse kinds of imprecision, uncertainty or inconsistency in the data models of a software system. The extension of existing programming and querying interfaces for the different aspects of information imperfection requires a proper modularization of the different concerns of numerical imprecision ha...
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ژورنال
عنوان ژورنال: Journal of Cheminformatics
سال: 2014
ISSN: 1758-2946
DOI: 10.1186/1758-2946-6-s1-p17