ABSTRACT
This paper describes the general design and application of CerBeruS, a computer-based system for supporting the process of sequential screening. CerBeruS stands for cluster-based selection, with cluster analysis forming the pivotal part of the system. CerBeruS uses the Ward's clustering method for partitioning the data set to be screened into smaller, more homogeneous subsets. One representative is picked from each subset and suggested as a screening candidate. Although the number of compounds submitted to screening is most often driven by the capacity of the assay, CerBeruS provides a statistical measure that computes the optimal number of clusters in the data set. This measure forms a point of reference for all screening experiments. Different hierarchies of subsets are stored in an Oracle database. Information about the size and content of a cluster can be retrieved from this database via a Visual Basic application. How these components work together in the CerBeruS system is demonstrated on a large data set. In addition, we show that, using the statistical measure, one can find an optimal trade-off between screening effort and number of hits.
