In the course of lectures, unique features of biological data are considered, leading to original statements of recognition and classification problems. It should be noted that for almost all the problems considered in the course, accurate and mathematically sound solutions have not yet been proposed. In this sense, the course represents an extensive field of activity for independent scientific work of students. A system of recognition tasks is formulated that reflects the structure of biological systems and provides a basis for the construction of problem-oriented theories. The fundamentals of the formalism developed to solve the problems of bioinformatics and other poorly formalized problems in the field of advanced biomedical research and sentiment analysis are considered. This formalism is based on the theory of universal and local constraints within the framework of an algebraic approach to recognition. Attention is paid to biomedical applications of the results of intelligent analysis of biological data.



Practical tasks will be announced during the lectures. Students can formulate the topics of research tasks themselves. After selecting the task, the work requirements are discussed.


Before the start of the oral exam (report-presentation), it is necessary to submit a report on the research work (3-5 pages) carried out on the selected task.


Machine learning methods.