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Ahnlichkeitsanalyse biologisch aktiver Molekiile mit durch Autokorrelationsvektoren trainierten selbstorganisierenden Karten
Bauknecht, Henri Zell, Andreas Bayer, Harald Levi, Paul Wagner, Markus Sadowski, Jens Gasteiger, Johann
Bauknecht, Henri
Zell, Andreas
Bayer, Harald
Levi, Paul
Wagner, Markus
Sadowski, Jens
Gasteiger, Johann
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Issue Date
1995
Submitted date
2024-05-29
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Abstract
Topological autocorrelation vectors can be used to estimate similarities of molecular structures. In the following paper we examinedifferent data sets of increasing size and complexity with this measure of similarity. All data sets contain substances with known biologicalactivity on the dopaminergic and benzodiazepine receptors. These two different classes of biological active substances can be separated by self-organizing maps, a kind of neural network well suited for clustering and visualization of similarity. The method is implemented on a massively parallel SIMD computer (MasPar MP-1) which is able to perform this analysis for databases of several thousand substances.
Citation
Bioinformatics - from nucleic acids and proteins to cell metabolism, 153 - 167
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Book chapter
conference paper
conference paper
Language
de
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Series/Report no.
GBF monographs ; Volume 18
ISSN
0930-4320
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ISBN
3527300724
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Attribution-NonCommercial-ShareAlike 4.0 International