Abstract
We propose to adapt an interval-based index structure, Relational Interval trees, to support the process of determining the structure of an unknown chemical compound. Important information for retrieving relevant substructures that make up a compound can only be described in an imprecise way, resulting in interval-based values specifying chemical shifts. The access method was implemented on top of a commercial database system and evaluated experimentally. The results of these experiments show that Relational Interval trees are an efficient way of indexing data needed for structure elucidation.
Keywords
- Structure Elucidation
- Nuclear Magnetic Resonance Spectroscopy
- Interval Tree
- Point Query
- Vector Approach
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Helmer, S. (2007). An Interval-Based Index Structure for Structure Elucidation in Chemical Databases. In: Melin, P., Castillo, O., Aguilar, L.T., Kacprzyk, J., Pedrycz, W. (eds) Foundations of Fuzzy Logic and Soft Computing. IFSA 2007. Lecture Notes in Computer Science(), vol 4529. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72950-1_62
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DOI: https://doi.org/10.1007/978-3-540-72950-1_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72917-4
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