Simple stochastic fingerprints towards mathematical modelling in biology and medicine. 1. The treatment of coccidiosis.

We have developed a classification function that is capable of discriminating between anticoccidial and nonanticoccidial compounds with different structural patterns. For this purpose, we calculated the Markovian electron delocalization negentropies of several compounds. These molecular descriptors, which act as molecular fingerprints, are derived from an electronegativity-weighted stochastic matrix (1Pi).

3D-MEDNEs: an alternative "in silico" technique for chemical research in toxicology. 1. prediction of chemically induced agranulocytosis.

A novel approach to molecular negentropy from the point of view of Markov models is introduced. Stochastic negentropies (MEDNEs) are used to develop a linear discriminant analysis. The discriminant analysis produced a set of two discriminant functions, which gave rise to a very good separation of 93.