Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: A Case study

OECD proposed five principles for validation of QSAR models used for regulatory purposes. We present a case study in Kohonen neural networks and counter propagation neural networks, which we have investigated whether these principles can be applied to models based on. The study is based on a counter propagation network built on toxicity of 541 compounds to the fish fathead minnow, and shows that most, if not all, of the OECD criteria can be met in modeling using this network approach

On 3-D Graphical Representation of DNA Primary Sequences and Their Numerical Characterization

In this article we (1) outline the construction of a 3-D “graphical” representation of DNA primary sequences, illustrated on a portion of the human â globin gene; (2) describe a particular scheme that transforms the above 3-D spatial representation of DNA into a numerical matrix representation; (3) illustrate construction of matrix invariants for DNA sequences; and (4) suggest a data reduction based on statistical analysis of matrix invariants generated for DNA. Each of the four contributions represents a novel development that we hope will facilitate comparative studies of DNA and open new directions for representation and characterization of DNA primary sequences