title: Self-Organizing Maps for In Silico Screening and Data Visualization.
abstract: Self-organizing maps, which are unsupervised artificial neural networks, have become a very useful tool in a wide area of disciplines, including medicinal chemistry. Here, we will focus on two applications of self-organizing maps: the use of self-organizing maps for in silico screening and for clustering and visualisation of large datasets. Additionally, the importance of parameter selection is discussed and some modifications to the original algorithm are summarised.
authors.affiliation: Department of Medicinal Chemistry, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria phone/fax: +43-1-4277-55110/+43-1-4277-9551.
authors.forename: Daniela
authors.initials: D
authors.lastname: Digles
authors.affiliation: Department of Medicinal Chemistry, University of Vienna, Althanstrasse 14, 1090 Vienna, Austria phone/fax: +43-1-4277-55110/+43-1-4277-9551. gerhard.f.ecker@univie.ac.at.
authors.forename: Gerhard F
authors.initials: GF
authors.lastname: Ecker
keywords: Chemoinformatics; Computational chemistry; Kohonen maps; Self-organizing maps; Virtual screening