Tuesday, May 18, 2021 15:00 MLIT Conference Hall, Online seminar via Webex Yuriy ButenkoDevelopment of information systems for theoretical and applied tasks on the basis of the HybriLIT platform The report gives an overview of two information systems (IS) under development on the basis of the HybriLIT platform. The main objective of creating these ISs is to automate calculations, as well as to provide data storage and analysis for different groups of researchers. The information system aimed at conducting radiobiological research provides tools for storing experimental data of different types and a software set for analyzing behavioral patterns of laboratory animals and for studying pathomorphological changes in the central nervous system after the exposure to ionizing radiation and other factors. The IS comprises blocks for storing and providing access to experimental data and a data analysis block based on machine and deep learning algorithms and computer vision algorithms. In addition, a virtual research environment (VRE) for modeling physical processes in complex systems derived from Josephson junctions is being developed on the basis of the HybriLIT platform. The VRE encompasses convenient tools based on web technologies for creating models and an interface for performing calculations on the HуbriLIT heterogeneous computing platform, as well as for visualizing calculation results, and provides different research groups with an environment for organizing joint studies, exchanging modules and calculation results. Alexey StadnikAlgorithms for the automation of processing data from experiments in the field of radiobiological research The report covers the results of the development of an algorithmic block of the information system being created within the joint project of MLIT and LRB on the automation of processing experimental data from radiobiological studies. A set of software tools for analyzing behavioral patterns of laboratory animals and studying pathomorphological changes in the central nervous system after the exposure to ionizing radiation and other factors is presented. Developed data analysis algorithms are based on machine and deep learning algorithms and computer vision algorithms. Experimental data analysis tasks embrace algorithms for video analysis and image analysis. Algorithms for the automated marking of the experimental field of the setup, the analysis of the characteristics of laboratory animals’ behavior during the experiment and the formation of summary information on the nature of animals’ behavior are developed within video analysis. Algorithms that comprise the segmentation and classification of neurons in the brain of laboratory animals, taking into account the noise present in the image, are elaborated for image analysis. The presented algorithms are implemented as components of the information system that provides different research groups with opportunities for analysis under joint studies. More information on the seminar and the link to connect via Webex are available at Indico.