Short-time fractal analysis of biological autoluminescence

Autor: Pavel Sovka, Martin Dlask, Michaela Poplová, Jaromir Kukal, Michal Cifra
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Luminescence
Photon
Computer science
Signal
Signal-to-noise ratio
Statistical Signal Processing
0303 health sciences
Signal processing
Data Processing
Multidisciplinary
Physics
030302 biochemistry & molecular biology
Process (computing)
Classical Mechanics
Eukaryota
Plants
Brownian bridge
Legumes
Fractal analysis
Fractals
Kernel (statistics)
Physical Sciences
Engineering and Technology
Medicine
Information Technology
Biological system
Elementary Particles
Research Article
Computer and Information Sciences
Beans
Science
030303 biophysics
Geometry
Germination
Fluid Mechanics
Continuum Mechanics
03 medical and health sciences
Signal to Noise Ratio
Particle Physics
Photons
Stochastic Processes
Series (mathematics)
Vigna
Organisms
Shot noise
Biology and Life Sciences
Fluid Dynamics
Probability Theory
Signal Processing
Brownian Motion
Mathematics
Statistical signal processing
Zdroj: PLoS ONE, Vol 14, Iss 7, p e0214427 (2019)
PLoS ONE
DOI: 10.1101/578286
Popis: Biological systems manifest continuous weak autoluminescence, which is present even in the absence of external stimuli. Since this autoluminescence arises from internal metabolic and physiological processes, several works suggested that it could carry information in the time series of the detected photon counts. However, there is little experimental work which would show any difference of this signal from random Poisson noise and some works were prone to artifacts due to lacking or improper reference signals. Here we apply rigorous statistical methods and advanced reference signals to test the hypothesis whether time series of autoluminescence from germinating mung beans display any intrinsic correlations. Utilizing the fractional Brownian bridge that employs short samples of time-series in the method kernel, we suggest that the detected autoluminescence signal from mung beans is not totally random, but it seems to involve a process with a negative memory. Our results contribute to the development of the rigorous methodology of signal analysis of photonic biosignals.
Databáze: OpenAIRE
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