Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis

This work is dedicated to developing enzyme biosensor software to solve problems regarding soil pollution analysis. An algorithm and specialised software have been developed which stores, analyses and visualises data using JavaScript programming language. The developed software is based on matching...

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Detalles Bibliográficos
Autores principales: Kratasyuk, Valentina A., Kolosova, Elizaveta M., Sutormin, Oleg S., Lonshakova-Mukina, Viktoriya I., Baygin, Matvey M., Rimatskaya, Nadezhda V., Sukovataya, Irina E., Shpedt, Alexander A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867351/
https://www.ncbi.nlm.nih.gov/pubmed/33540862
http://dx.doi.org/10.3390/s21031017
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author Kratasyuk, Valentina A.
Kolosova, Elizaveta M.
Sutormin, Oleg S.
Lonshakova-Mukina, Viktoriya I.
Baygin, Matvey M.
Rimatskaya, Nadezhda V.
Sukovataya, Irina E.
Shpedt, Alexander A.
author_facet Kratasyuk, Valentina A.
Kolosova, Elizaveta M.
Sutormin, Oleg S.
Lonshakova-Mukina, Viktoriya I.
Baygin, Matvey M.
Rimatskaya, Nadezhda V.
Sukovataya, Irina E.
Shpedt, Alexander A.
author_sort Kratasyuk, Valentina A.
collection PubMed
description This work is dedicated to developing enzyme biosensor software to solve problems regarding soil pollution analysis. An algorithm and specialised software have been developed which stores, analyses and visualises data using JavaScript programming language. The developed software is based on matching data of 51 non-commercial standard soil samples and their inhibitory effects on three enzyme systems of varying complexity. This approach is able to identify the influence of chemical properties soil samples, without toxic agents, on enzyme biosensors. Such software may find wide use in environmental monitoring.
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spelling pubmed-78673512021-02-07 Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis Kratasyuk, Valentina A. Kolosova, Elizaveta M. Sutormin, Oleg S. Lonshakova-Mukina, Viktoriya I. Baygin, Matvey M. Rimatskaya, Nadezhda V. Sukovataya, Irina E. Shpedt, Alexander A. Sensors (Basel) Communication This work is dedicated to developing enzyme biosensor software to solve problems regarding soil pollution analysis. An algorithm and specialised software have been developed which stores, analyses and visualises data using JavaScript programming language. The developed software is based on matching data of 51 non-commercial standard soil samples and their inhibitory effects on three enzyme systems of varying complexity. This approach is able to identify the influence of chemical properties soil samples, without toxic agents, on enzyme biosensors. Such software may find wide use in environmental monitoring. MDPI 2021-02-02 /pmc/articles/PMC7867351/ /pubmed/33540862 http://dx.doi.org/10.3390/s21031017 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Communication
Kratasyuk, Valentina A.
Kolosova, Elizaveta M.
Sutormin, Oleg S.
Lonshakova-Mukina, Viktoriya I.
Baygin, Matvey M.
Rimatskaya, Nadezhda V.
Sukovataya, Irina E.
Shpedt, Alexander A.
Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
title Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
title_full Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
title_fullStr Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
title_full_unstemmed Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
title_short Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis
title_sort software for matching standard activity enzyme biosensors for soil pollution analysis
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7867351/
https://www.ncbi.nlm.nih.gov/pubmed/33540862
http://dx.doi.org/10.3390/s21031017
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