It allows both unsupervised (Kohonen) and supervised learning (counterpropagation network)
and provides many techniques for the visualization of chemical data.

SONNIA has the following features: "); close_paragraph(); print_title("Applications", $font2, 2, 0); open_paragraph(); print(" SONNIA has shown to be applicable in the following fields "); close_paragraph(); /* print_title("Online-Access", $font2, 2, 0); open_paragraph(); print("

Read a short introduction or go directly to the input forms (use buttons above):

It is possible to run the calculations for a molecule drawn by an interactive molecule editor
to get all properties calculated by PETRA for datasets of up to $uploadLimit molecules via upload of a datafile "); close_paragraph(); */ print_title("Availability", $font2, 2, 0); open_paragraph(); print(" SONNIA is available for various Unix derivatives: Please contact Prof. Gasteiger if you are interested in evaluation of the program. "); close_paragraph(); /* and our web interface is * not sufficient for your purpose. */ /* print_title("Development", $font2, 2, 0); open_paragraph(); print(" The current work focusses on the development of a QSPR model for the prediction of pKa values that will be available within the next version 3.1 to be released end of summer 2001.
The approach we will integrate in PETRA bases on the quantification of the physicochemical effects that have an influence on the pKa and the derivation of a quantitative model using a feed forward neural network with a back-propagation learning algorithm.
In an initial model we have shown the high predictive power of this approach as presented at the \"New Approaches in Drug Design and Discovery\"-Workshop, Rauischholzhausen March 2001. "); close_paragraph(); */ print_title("Publications", $font2, 2, 0); open_paragraph(); print(" J. Zupan, J. Gasteiger,
\"Neural Networks in Chemistry and Drug Desgin\",
Second Edition, Wiley-VCH, Weinheim, 1999, ISBN 3-527-29779-0.

S. Anzali, J. Gasteiger, U. Holzgrabe, J. Polanski, J. Sadowski, A. Teckentrup, M. Wagener,
\"The Use of Self-Organizing Neural Networks in Drug Design.\"
In \"3D QSAR in Drug Design -Volume 2\";
H. Kubinyi, G. Folkers, Y.C. Martin (Eds.) Kluwer/ESCOM, Dordrecht, NL, 1998, pp 273-299. "); close_paragraph(); /* J. Gasteiger, \"Empirical Methods for the Calculation of Physicochemical Data of Organic Compounds\",
in: \"Physical Property Prediction in Organic Chemistry\",
Ed. C. Jochum, M. G. Hicks, J. Sunkel, Springer Verlag, Heidelberg, 119-138, 1988

See a comprehensive list of publications about the calculation of in organic compounds. */ /* print_title("Manual", $font2, 2, 0); open_paragraph(); print(" The manual is online available in HTML,
or downloadable as PDF-File. "); close_paragraph(); */ /* print_title("Slide Show", $font2, 2, 0); open_paragraph(); close_paragraph(); */ print_title("Contact", $font2, 2, 0); open_paragraph(); print(" If you are interested in SONNIA please contact:
   1. Prof. Johann Gasteiger
   2. Dr. Lothar Terfloth
"); close_paragraph(); print_footer($lastChange, $KMAPHomeUrl, $counterFile, "home"); close_document();