Simulation modelling and data mining approach for the study of applied fluorescence spectroscopy systems

Abstract

For the study of biomolecular compounds in applied fluorescence spectroscopy supporting systems an integrated approach, based on simulation modelling and data mining methods and including simulation models of physical processes, methods and algorithms for data mining, and software for studying molecular and cellular systems is proposed. The idea of an integrated approach is in using simulation modelling of biophysical processes occurring in the object of study, selecting the most informative experimental data, and determining the characteristics of the object using data mining algorithms. The effectiveness of the algorithms of the proposed approach is verified by analysing simulated and experimental data of fluorescence spectroscopy systems. As a practical implementation of the developed integrated methodology, the computational platform FluorSimStudio was developed for processing time-resolved fluorescence measurements. The digital platform is an open system and allows addition of complex analysis models, taking into account the development of new modelling and data processing algorithms. The use of complex analysis improves the efficiency of studying biophysical systems during big data analysis.