Self-Organizing Neural Networks for Screening and Development of Novel Artificial Sweetener Candidates

Title: Self-Organizing Neural Networks for Screening and Development of Novel Artificial Sweetener Candidates

Volume: 3 Issue: 6

Author(s): Jaroslaw Polanski, Johann Gasteiger and Krystyna Jarzembek

Affiliation:

Abstract: The use of Kohonen feature maps for the visualization of various aspects of molecular similarity is briefly reviewed and illustrated. It is shown that a specific feature of self-organizing maps (SOM) makes them of special interest for the screening of compounds. In particular, these methods were used to design candidates for new sweeteners, which were then synthesized.

Cite this article as:

Polanski Jaroslaw, Gasteiger Johann and Jarzembek Krystyna, Self-Organizing Neural Networks for Screening and Development of Novel Artificial Sweetener Candidates, Combinatorial Chemistry & High Throughput Screening 2000; 3 (6) . https://dx.doi.org/10.2174/1386207003331427

DOI https://dx.doi.org/10.2174/1386207003331427	Print ISSN 1386-2073
Publisher Name Bentham Science Publisher	Online ISSN 1875-5402