Method for Processing Fluorescence Decay Kinetic Curves Using Data Mining Algorithms
| Autor: | Victor V. Skakun, Mikalai M. Yatskou, Vladimir V. Apanasovich |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Dimensionality reduction
010401 analytical chemistry Experimental data 02 engineering and technology 021001 nanoscience & nanotechnology Condensed Matter Physics Space (mathematics) Kinetic energy 01 natural sciences Fluorescence Medoid Fluorescence spectroscopy 0104 chemical sciences Set (abstract data type) 0210 nano-technology Biological system Spectroscopy Mathematics |
| Zdroj: | Journal of Applied Spectroscopy. 87:333-344 |
| ISSN: | 1573-8647 0021-9037 |
| Popis: | A method is proposed for processing large data sets of fluorescence decay kinetic curves using data mining algorithms to determine the parameters of biophysical and optical processes in molecular systems. The idea of this method involves breaking the initial set of fluorescence decay curves into clusters in terms of some degree of similarity, finding medoids of the clusters, applying a dimensionality reduction method to the data and imaging the experimental data in two- and three-dimensional space, and analyzing the decay curves of the medoids using analytic or simulation models. The applicability of the method is examined for the example of analyzing sets of data representing systems of fluorophores. This method requires substantially less time and calculations of the analytic approximation functions, while the accuracy of the estimated parameters is higher than in the classical approach. |
| Databáze: | OpenAIRE |
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