Open AccessDevelopment of computer modeling methods in proteomics
Author(s) -
Yu. B. Olevska,
V. I. Olevskyi,
O. V. Olevskyi
Publication year - 2020
Publication title -
komp'ûterne modelûvannâ: analìz, upravlìnnâ, optimìzacìâ
Language(s) - English
Resource type - Journals
eISSN - 2617-6092
pISSN - 2521-6406
DOI - 10.32434/2521-6406-2020-8-2-49-58
Subject(s) - fuzzy logic , computer science , defuzzification , field (mathematics) , data mining , fuzzy mathematics , identification (biology) , sample (material) , artificial intelligence , fuzzy control system , fuzzy set , machine learning , fuzzy classification , fuzzy number , mathematics , chemistry , botany , chromatography , pure mathematics , biology
The need for modern research in the field of biomedical sciences is to solve the problem of improving the accuracy of the results of electrophoretography in their common form and substantiating the conclusions based on such experiments, in particular, increasing the accuracy of protein identification. Calculation problems in this direction are solved by both universal and specialized computer systems, the variety of which is due, firstly, to the specific needs of the natural sciences, and, secondly, by the mathematical apparatus that is used for fairly voluminous calculations. Usually, in this case, methods of mathematical statistics are used, but in this case the use of stochastic data analysis was not sufficiently correct due to the lack of a representative sample or its heterogeneity. In connection with these needs, a computer package FANSPREL – «Fuzzy ANalysis System for Protein Electrophoresis» was created for processing electrophoregrams and identifying proteins using fuzzy mathematics methods based on algorithms developed by the authors in previous studies. An approach is proposed based on the determination of a fuzzy scale based on the results of processing fuzzy data of known proteins, recognition of proteins obtained from the results of research, and comparison of proteins among themselves based on the results of experiments. The mathematical part of the information system is the construction of an approximation of the membership function based on the obtained data of a curve with four parameters and the construction of a fuzzy scale model, determination of fuzzy masses of proteins and their comparison by conjunction of fuzzy values, and subsequent defuzzification of the results. The system makes it possible to more accurately identify proteins, in particular to distinguish between those whose masses were identified as the same with other forms of processing with a certain accuracy or an undefined result was obtained. The program has a user-friendly interface, provides a standard form of input and output data, and is tested for solving problems of experiments that took place for the immediate needs of agriculture, in particular to improve various types of soil that is used to grow corn. Keywords: fuzzy modeling, electrophoregrams, computer system.