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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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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.
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Date
1995
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GBF Gesellschaft für Biotechnologische Forschung mbH, Braunschweig
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Bioinformatics - from nucleic acids and proteins to cell metabolism, 153 - 167