Data analysis in complex biomolecular systems
The biomolecular technology progress is directly related to the development of effective methods and algorithms for processing a large amount of information obtained by modern high-throughput experimental equipment. The priority task is the development of promising computational tools for the analys...
| Main Authors: | , |
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| Format: | Article |
| Language: | Russian |
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The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
2021-03-01
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| Series: | Informatika |
| Subjects: | |
| Online Access: | https://inf.grid.by/jour/article/view/1110 |
| _version_ | 1797877217552760832 |
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| author | M. M. Yatskou V. V. Apanasovich |
| author_facet | M. M. Yatskou V. V. Apanasovich |
| author_sort | M. M. Yatskou |
| collection | DOAJ |
| description | The biomolecular technology progress is directly related to the development of effective methods and algorithms for processing a large amount of information obtained by modern high-throughput experimental equipment. The priority task is the development of promising computational tools for the analysis and interpretation of biophysical information using the methods of big data and computer models. An integrated approach to processing large datasets, which is based on the methods of data analysis and simulation modelling, is proposed. This approach allows to determine the parameters of biophysical and optical processes occurring in complex biomolecular systems. The idea of an integrated approach is to use simulation modelling of biophysical processes occurring in the object of study, comparing simulated and most relevant experimental data selected by dimension reduction methods, determining the characteristics of the investigated processes using data analysis algorithms. The application of the developed approach to the study of bimolecular systems in fluorescence spectroscopy experiments is considered. The effectiveness of the algorithms of the approach was verified by analyzing of simulated and experimental data representing the systems of molecules and proteins. The use of complex analysis increases the efficiency of the study of biophysical systems during the analysis of big data. |
| first_indexed | 2024-04-10T02:13:40Z |
| format | Article |
| id | doaj.art-2018c7a47f664c7797208b8e6bcc337b |
| institution | Directory Open Access Journal |
| issn | 1816-0301 |
| language | Russian |
| last_indexed | 2024-04-10T02:13:40Z |
| publishDate | 2021-03-01 |
| publisher | The United Institute of Informatics Problems of the National Academy of Sciences of Belarus |
| record_format | Article |
| series | Informatika |
| spelling | doaj.art-2018c7a47f664c7797208b8e6bcc337b2023-03-13T08:32:24ZrusThe United Institute of Informatics Problems of the National Academy of Sciences of BelarusInformatika1816-03012021-03-0118110512210.37661/1816-0301-2021-18-1-105-122963Data analysis in complex biomolecular systemsM. M. Yatskou0V. V. Apanasovich1Belarusian State UniversityBelarusian State UniversityThe biomolecular technology progress is directly related to the development of effective methods and algorithms for processing a large amount of information obtained by modern high-throughput experimental equipment. The priority task is the development of promising computational tools for the analysis and interpretation of biophysical information using the methods of big data and computer models. An integrated approach to processing large datasets, which is based on the methods of data analysis and simulation modelling, is proposed. This approach allows to determine the parameters of biophysical and optical processes occurring in complex biomolecular systems. The idea of an integrated approach is to use simulation modelling of biophysical processes occurring in the object of study, comparing simulated and most relevant experimental data selected by dimension reduction methods, determining the characteristics of the investigated processes using data analysis algorithms. The application of the developed approach to the study of bimolecular systems in fluorescence spectroscopy experiments is considered. The effectiveness of the algorithms of the approach was verified by analyzing of simulated and experimental data representing the systems of molecules and proteins. The use of complex analysis increases the efficiency of the study of biophysical systems during the analysis of big data.https://inf.grid.by/jour/article/view/1110biomolecular systembiophysical processessimulation modellingdata analysistime-resolved fluorescence spectroscopyfluorescence fluctuation spectroscopy |
| spellingShingle | M. M. Yatskou V. V. Apanasovich Data analysis in complex biomolecular systems Informatika biomolecular system biophysical processes simulation modelling data analysis time-resolved fluorescence spectroscopy fluorescence fluctuation spectroscopy |
| title | Data analysis in complex biomolecular systems |
| title_full | Data analysis in complex biomolecular systems |
| title_fullStr | Data analysis in complex biomolecular systems |
| title_full_unstemmed | Data analysis in complex biomolecular systems |
| title_short | Data analysis in complex biomolecular systems |
| title_sort | data analysis in complex biomolecular systems |
| topic | biomolecular system biophysical processes simulation modelling data analysis time-resolved fluorescence spectroscopy fluorescence fluctuation spectroscopy |
| url | https://inf.grid.by/jour/article/view/1110 |
| work_keys_str_mv | AT mmyatskou dataanalysisincomplexbiomolecularsystems AT vvapanasovich dataanalysisincomplexbiomolecularsystems |