Paper
9 April 2020 Study of statistical properties of GB-speckles, part I: laser speckles generated on the nucleotide sequences of the gatA gene of Chlamydia trachomatis strains isolated in the Republic of Belarus
Valentina Feodorova, Yury Saltykov, Liudmila Rubanik, Nikolay Poleschuk, Alexander Ulyanov, Sergey Zaytsev, Onega Ulianova, Sergey Ulyanov
Author Affiliations +
Proceedings Volume 11457, Saratov Fall Meeting 2019: Optical and Nano-Technologies for Biology and Medicine; 114571X (2020) https://doi.org/10.1117/12.2563642
Event: Saratov Fall Meeting 2019: VII International Symposium on Optics and Biophotonics, 2019, Saratov, Russian Federation
Abstract
As it has been demonstrated earlier, different types of re-coding of bacterial nucleotide sequences to gene-based specklepatterns (GB-speckles) can be used. In this paper an advanced study, devoted to optimization of this algorithm, is presented. With this purpose, investigations of statistical properties of the GB-speckles, generated on the nucleotide sequences of the gatA gene of Chlamydia trachomatis has been performed. The first- and second-order statistics of intensity fluctuations in GB-speckles have been analyzed. Perspectives of the gene identification using a statistical analysis of the homologous laser GB-speckles have been demonstrated. The analyzed nucleotide sequences of the gatA gene of C. trachomatis strains isolated in the Republic of Belarus were compared with those recently isolated in Russian Federation.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Valentina Feodorova, Yury Saltykov, Liudmila Rubanik, Nikolay Poleschuk, Alexander Ulyanov, Sergey Zaytsev, Onega Ulianova, and Sergey Ulyanov "Study of statistical properties of GB-speckles, part I: laser speckles generated on the nucleotide sequences of the gatA gene of Chlamydia trachomatis strains isolated in the Republic of Belarus", Proc. SPIE 11457, Saratov Fall Meeting 2019: Optical and Nano-Technologies for Biology and Medicine, 114571X (9 April 2020); https://doi.org/10.1117/12.2563642
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KEYWORDS
Statistical analysis

Bioinformatics

Correlation function

Genetic algorithms

Microbiology

Macromolecules

MATLAB

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