ИСТИНА

Invited lecture was devoted to the challenging problem in modern Medicine is to estimate the risks of complex diseases for individuals taking into account their SNP (single nucleotide polymorphisms) data and also the environmental factors. On this way the main achievements are based on the deep results established in bioinformatics, artificial intelligence, econometrics and mathematical statistics. In development of recent papers the main attention will be paid to the new version of the MDR-method, various modifications of logic regression and machine learning methods. New theorems are proved to justify different methods of data analysis in the framework of specified stochastic models. In particular, we discuss the identification of the most significant combinations of genetic and nongenetic factors which could increase the risk of a disease. We apply the techniques of random trees and stochastic optimization as well as random fields theory. The applications to analysis of cardio-vascular diseases are provided. For this aim the supercomputer “Chebyshev” (MSU) was employed.