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Developing the control criterion for a continuous culture of microorganisms / V. V. Adamovich, D. Yu. Rogozin, A. G. Degermendzhi // Mikrobiologiya. - 2005. - Vol. 74, Is. 1. - С. 5-16 . - ISSN 0026-3656
Кл.слова (ненормированные):
Chemostat -- Control criterion -- Control factor -- Microorganism population -- Sensitivity coefficients -- algorithm -- bacterium -- biological model -- biomass -- culture medium -- ecosystem -- growth, development and aging -- methodology -- microbiological examination -- review -- Algorithms -- Bacteria -- Bacteriological Techniques -- Biomass -- Culture Media -- Ecosystem -- Models, Biological
Аннотация: A short survey and critical analysis of previously proposed criteria for growth control of populations of microorganisms in the chemostat are presented. Based on the analysis of a mathematical model of the steady-state of a microbial population in the chemostat, an adequate control criterion is suggested, along with a method to identify the corresponding regulating factors. The new control criterion is expressed as a product of the factor transformation coefficient and the biomass sensitivity coefficient (SC) with respect to the change of the factor at the chemostat inlet (referred to in the sequel as the biomass SC). The control criterion determines the strength of the control exerted by this or that factor. The method of determination of the regulating factors consists in experimental determination of the real SCs for factors and the biomass and in calculating on this basis the corresponding ideal SCs for constant factor transformation coefficients. The ideal SCs are shown to add up to an integer value, a constraint that we call "quantization" relationships. Such relationships are used to test the completeness of the drawn list of control factors. The proposed method was applied to our own and literature data.

Scopus
Держатели документа:
Institute of Biophysics, Siberian Division, Russian Academy of Sciences, Krasnoyarsk, 660036, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Adamovich, V.V.; Rogozin, D.Yu.; Degermendzhi, A.G.

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Challenges and opportunities for integrating lake ecosystem modelling approaches / W. M. Mooij [et al.] // Aquatic Ecology. - 2010. - Vol. 44, Is. 3. - P633-667, DOI 10.1007/s10452-010-9339-3 . - ISSN 1386-2588
Кл.слова (ненормированные):
Adaptive processes -- Analysis -- Aquatic -- Bifurcation -- Biodiversity -- Climate warming -- Community -- Eutrophication -- Fisheries -- Food web dynamics -- Freshwater -- Global change -- Hydrology -- Lake -- Management -- Marine -- Mitigation -- Model integration -- Model limitations -- Non-linear dynamics -- Nutrients -- Plankton -- Population -- Prediction -- Spatial -- Understanding -- adaptive management -- algorithm -- aquatic community -- biodiversity -- ecosystem modeling -- eutrophication -- fishery production -- food web -- fuzzy mathematics -- global warming -- hydrology -- lake ecosystem -- mitigation -- model test -- numerical model -- nutrient availability -- plankton -- prediction -- saline lake -- spatial analysis
Аннотация: A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models. В© 2010 The Author(s).

Scopus
Держатели документа:
Netherlands Institute of Ecology (NIOO-KNAW), Department of Aquatic Ecology, Rijksstraatweg 6, 3631 AC Nieuwersluis, Netherlands
Aarhus University, National Environmental Research Institute, Department of Freshwater Ecology, 8600 Silkeborg, Denmark
Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Kivioq 2, P.O. Box 570, 3900 Nuuk, Greenland
University of Toronto, Department of Physical and Environmental Sciences, Toronto, ON M1C 1A4, Canada
Institute of Computational Modelling (SB-RAS), Siberian Federal University, 660036 Krasnoyarsk, Russian Federation
Tanzania Fisheries Research Institute (TAFIRI), Mwanza Centre, P.O. Box 475, Mwanza, Tanzania
Institute of Biophysics (SB-RAS), Akademgorodok, 660036 Krasnoyarsk, Russian Federation
University of Miami, Florida Integrated Science Centre, USGS, Coral Gables, FL 33124, United States
Wageningen University, Department of Aquatic Ecology and Water Quality, P.O. Box 47, 6700 AA Wageningen, Netherlands
Centre for Ecology and Hydrology, Lancaster Environment Centre, Lake Ecosystem Group, Algal Modelling Unit, Bailrigg, Lancaster LA1 4AP England, United Kingdom
Federal University of Alagoas, Centre for Technology, Campus A.C. Simoes, 57072-970 Maceio-AL, Brazil
Institute of Biochemistry and Biology, Department of Ecology and Ecosystem Modelling, University of Potsdam, Am Neuen Palais 10, 14469 Potsdam, Germany
Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment, P.O. Box 7050, 75007 Uppsala, Sweden
University of Waikato, Centre for Biodiversity and Ecology Research, Private Bag 3105, Hamilton, New Zealand
University of Western Australia, School of Earth and Environment, Crawley, WA 6009, Australia
Technische Universitat Dresden, Institute of Hydrobiology, 01062 Dresden, Germany
Technische Universitat Dresden, Neunzehnhain Ecological Station, Neunzehnhainer Str. 14, 09514 Lengefeld, Germany
Deltares, P.O. Box 177, 2600 MH Delft, Netherlands
Technion-Israel Institute of Technology, Faculty of Civil and Environmental Engineering, Technicon City, Haifa 32000, Israel
Helmholtz Centre for Environmental Research, Department of Lake Research, Brueckstrasse 3a, 39114 Magdeburg, Germany
Witteveen and Bos, P.O. Box 233, 7400 AV Deventer, Netherlands
University of Oslo, Department of Biology, P.O. Box 1066, Blindern, 0316 Oslo, Norway
UNESCO-IHE Institute of Water Education, 2601 DA Delft, Netherlands
Portland State University, Department of Civil and Environmental Engineering, Portland, OR 97207, United States
Netherlands Environmental Assessment Agency (PBL), P.O. Box 303, 3720 AH Bilthoven, Netherlands : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Mooij, W.M.; Trolle, D.; Jeppesen, E.; Arhonditsis, G.; Belolipetsky, P.V.; Chitamwebwa, D.B.R.; Degermendzhy, A.G.; DeAngelis, D.L.; De Senerpont Domis, L.N.; Downing, A.S.; Elliott, J.A.; Fragoso Jr., C.R.; Gaedke, U.; Genova, S.N.; Gulati, R.D.; Hakanson, L.; Hamilton, D.P.; Hipsey, M.R.; 't Hoen, J.; Hulsmann, S.; Los, F.H.; Makler-Pick, V.; Petzoldt, T.; Prokopkin, I.G.; Rinke, K.; Schep, S.A.; Tominaga, K.; van Dam, A.A.; van Nes, E.H.; Wells, S.A.; Janse, J.H.

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The "quantization" of sensitivity coefficients is preserved in microbial populations heterogeneous with respect to growth rate and age / V. M. Nekrasov, A. V. Chernychev, A. G. Degermendzhy // Doklady Biological Sciences. - 2006. - Vol. 406, Is. 1-6. - P91-93, DOI 10.1134/S0012496606010261 . - ISSN 0012-4966
Кл.слова (ненормированные):
algorithm -- article -- bacterium -- biodiversity -- growth, development and aging -- population dynamics -- theoretical model -- time -- Algorithms -- Bacteria -- Biodiversity -- Models, Theoretical -- Population Dynamics -- Time Factors

Scopus
Держатели документа:
Institute of Chemical Kinetics and Combustion, Siberian Division, Russian Academy of Sciences, Institutskaya ul. 3, Novosibirsk, 630090, Russian Federation
Institute of Biophysics, Siberian Division, Russian Academy of Sciences, Akademgorodok, Krasnoyarsk, 660036, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Nekrasov, V.M.; Chernychev, A.V.; Degermendzhy, A.G.

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Study of Ralstonia eutropha culture producing polyhydroxyalkanoates on products of coal processing / T. G. Volova, N. A. Voinov // Prikladnaia biokhimiia i mikrobiologiia. - 2004. - Vol. 40, Is. 3. - С. 296-300 . - ISSN 0555-1099
Кл.слова (ненормированные):
carbon monoxide -- coal -- polyester -- antibiotic resistance -- article -- culture medium -- enzyme specificity -- gas -- growth, development and aging -- metabolism -- microbiology -- Wautersia eutropha -- Carbon Monoxide -- Coal -- Culture Media -- Cupriavidus necator -- Drug Resistance, Microbial -- Gases -- Polyesters -- Substrate Specificity
Аннотация: Kinetic indices of growth, polyhydroxyalkanoate (PHA) accumulation, and gas exchange have been studied in a culture of the carbon monoxide-resistant hydrogen strain Ralstonia eutropha B-5786 grown on a gaseous substrate (GS) obtained by lignite gasification. The GS was shown to be suitable for PHA production. To increase the degree of GS consumption, various modes of gas supply to the culture were tested. Based on the results, an algorithm was developed for calculating and controlling gas-exchange parameters in the PHA-accumulating culture of Ralstonia eutropha, grown on a new GS allowing high polymer yields (up to 75%) and degrees of the substrate utilization (up to 90%).

Scopus
Держатели документа:
Institute of Biophysics, Siberian Division of the Russian Academy of Sciences, Krasnoyarsk, 660036 Russia. : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Volova, T.G.; Voinov, N.A.

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Study of a Ralstonia eutropha culture producing polyhydroxyalkanoates on products of coal processing / T. G. Volova, N. A. Voinov // Applied Biochemistry and Microbiology. - 2004. - Vol. 40, Is. 3. - P249-252, DOI 10.1023/B:ABIM.0000025946.47013.03 . - ISSN 0003-6838
Кл.слова (ненормированные):
alkanoic acid -- carbon monoxide -- coal -- hydrogen -- lignite -- algorithm -- article -- bacterial strain -- bacterium culture -- coal gasification -- controlled study -- gas -- gas exchange -- mathematical computing -- nonhuman -- Ralstonia eutropha -- Bacteria (microorganisms) -- Ralstonia -- Wautersia eutropha
Аннотация: Kinetic indices of growth, polyhydroxyalkanoate (PHA) accumulation, and gas exchange were studied in a culture of the carbon monoxide-resistant hydrogen strain Ralstonia eutropha B-5786 grown on a gaseous substrate (GS) obtained by lignite gasification. The GS was shown to be suitable for PHA production. To increase the degree of GS consumption, various modes of gas supply to the culture were tested. Based on the results, an algorithm was developed for calculating and controlling gas-exchange parameters in the PHA-accumulating culture of Ralstonia eutropha, grown on a new GS allowing high polymer yields (up to 75%) and degrees of substrate utilization (up to 90%).

Scopus
Держатели документа:
Institute of Biophysics, Siberian Div. Russ. Acad. of Sci., Krasnoyarsk, 660036, Russian Federation
Siberian State Technol. University, Min. of Educ. of the Russ. Fed., Krasnoyarsk, 660049, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Volova, T.G.; Voinov, N.A.

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Mathematical model of seasonal agrophytocenosis productivity based on terrestrial and satellite monitoring / T. I. Pisman [et al.] // Doklady Biological Sciences. - 2009. - Vol. 428, Is. 1. - P467-470, DOI 10.1134/S0012496609050226 . - ISSN 0012-4966
Кл.слова (ненормированные):
agriculture -- algorithm -- article -- biological model -- biomass -- computer simulation -- crop -- growth, development and aging -- methodology -- season -- space flight -- wheat -- Agriculture -- Algorithms -- Biomass -- Computer Simulation -- Crops, Agricultural -- Models, Biological -- Seasons -- Spacecraft -- Triticum

Scopus
Держатели документа:
Institute of Biophysics, Siberian Branch, Russian Academy of Sciences, Akademgorodok 50.50, Krasnoyarsk 660036, Russian Federation
Institute of Natural Sciences and Mathematics, Khakass State University, pr. Lenina 90, Abakan, 655000 Khakassia, Russian Federation
Institute of Space and Information Technologies, Siberian Federal University, ul. Kirenskogo 26, Krasnoyarsk 660074, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Pisman, T.I.; Pugacheva, I.Y.; Jukova, E.Y.; Shevyrnogov, A.P.

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Mathematical model of the interaction of components in a plant-rhizospheric microorganisms system at the higher level of carbon dioxide in atmosphere / T. I. Pis'man, L. A. Somova, N. S. Pechurkin // Biofizika. - 2002. - Vol. 47, Is. 5. - С. 920-925 . - ISSN 0006-3029
Кл.слова (ненормированные):
carbon dioxide -- algorithm -- article -- biological model -- biomass -- ecosystem -- microbiology -- physiology -- plant seed -- Pseudomonas putida -- wheat -- Algorithms -- Biomass -- Carbon Dioxide -- Ecosystem -- Models, Biological -- Pseudomonas putida -- Seeds -- Triticum
Аннотация: A mathematical model describing the interaction of plants and rhizospheric microorganisms on complete mineral medium at a higher CO2 level in the atmosphere was constructed. The positive effect of CO2-enrichment on the system plant--rhizospheric microorganisms was shown. The effect of rhizospheric microorganisms on plant growth at normal and high level of carbon dioxide was demonstrated. It was shown that the biomass of plant in the system is smaller than the biomass of plant growing without microorganisms. It was experimentally demonstrated that a simple ecosystem wheat--Pseudomonas putida--artificial soil develops and functions differently than its individual constituents in the case of a wheat-artificial soil system. With unlimited nutrition and a higher CO2 level (0.06%), plants with roots inoculated with microorganisms have a smaller biomass than plants that were not inoculated with microorganisms.

Scopus
Держатели документа:
Institute of Biophysics, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, 660036 Russia. : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Pis'man, T.I.; Somova, L.A.; Pechurkin, N.S.

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Study of a Ralstonia eutropha culture producing polyhydroxyalkanoates on products of coal processing [Text] / T. G. Volova, N. A. Voinov // Appl. Biochem. Microbiol. - 2004. - Vol. 40, Is. 3. - P. 249-252, DOI 10.1023/B:ABIM.0000025946.47013.03. - Cited References: 18 . - ISSN 0003-6838

РУБ Biotechnology & Applied Microbiology + Microbiology

Аннотация: Kinetic indices of growth, polyhydroxyalkanoate (PHA) accumulation, and gas exchange were studied in a culture of the carbon monoxide-resistant hydrogen strain Ralstonia eutropha B-5786 grown on a gaseous substrate (GS) obtained by lignite gasification. The GS was shown to be suitable for PHA production. To increase the degree of GS consumption, various modes of gas supply to the culture were tested. Based on the results, an algorithm was developed for calculating and controlling gas-exchange parameters in the PHA-accumulating culture of Ralstonia eutropha, grown on a new GS allowing high polymer yields (up to 75%) and degrees of substrate utilization (up to 90%).

WOS
Держатели документа:
Russian Acad Sci, Siberian Div, Inst Biophys, Krasnoyarsk 660036, Russia
Siberian State Technol Univ, Minist Educ Russian Federat, Krasnoyarsk 660049, Russia
ИБФ СО РАН : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Volova, T.G.; Voinov, N.A.

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Predicting the state of the Earth's ozone layer for different time intervals with the use of neural networks [Text] / V. B. Kashkin, Y. P. Lankin, I. Y. Sakash // Izv. Atmos. Ocean. Phys. - 2005. - Vol. 41, Is. 4. - P. 469-475. - Cited References: 10 . - ISSN 0001-4338

РУБ Meteorology & Atmospheric Sciences + Oceanography
Рубрики:
ERRORS
Аннотация: The problems of studying and simulating the Earth's ozone layer are discussed. It is shown that the construction of models for the total ozone content (TOC) in the stratosphere with the use of neural networks is promising. The neural-network algorithm used is described. TOC forecasts for different time periods are made using neuronetwork models.

WOS
Держатели документа:
Krasnoyarsk State Tech Univ, Krasnoyarsk 660074, Russia
Russian Acad Sci, Inst Biophys, Siberian Div, Krasnoyarsk 660036, Russia
ИБФ СО РАН : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Kashkin, V.B.; Lankin, Y.P.; Sakash, I.Y.

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10.

Application of Enzyme Bioluminescence in Ecology [Text] / E. Esimbekova, V. Kratasyuk, O. Shimomura // Adv. Biochem. Eng. Biotechnol. : SPRINGER-VERLAG BERLIN, 2014. - Vol. 144. - P67-109. - (Advances in Biochemical Engineering-Biotechnology), DOI 10.1007/978-3-662-43385-0_3. - Cited References:85 . -

РУБ Biotechnology & Applied Microbiology
Рубрики:
BACTERIAL LUCIFERASE
   IN-VITRO
   PYRETHROID INSECTICIDES
   FRESH-WATER
Кл.слова (ненормированные):
Bioluminescence -- Ecological monitoring -- Enzymatic assay -- Immobilization -- Integral water toxicity -- Luciferase
Аннотация: This review examines the general principles of bioluminescent enzymatic toxicity bioassays and describes the applications of these methods and the implementation in commercial biosensors. Bioluminescent enzyme system technology (BEST) has been proposed in the bacterial coupled enzyme system, wherein NADH: FMN-oxidoreductase-luciferase substitutes for living organisms. BEST was introduced to facilitate and accelerate the development of cost-competitive enzymatic systems for use in biosensors for medical, environmental, and industrial applications. For widespread use of BEST, the multicomponent reagent "Enzymolum'' has been developed, which contains the bacterial luciferase, NADH: FMN-oxidoreductase, and their substrates, co-immobilized in starch or gelatin gel. Enzymolum is the central part of Portable Laboratory for Toxicity Detection (PLTD), which consists of a biodetector module, a sampling module, a sample preparation module, and a reagent module. PLTD instantly signals chemical-biological hazards and allows us to detect a wide range of toxic substances. Enzymolum can be integrated as a biological module into the portable biodetector-biosensor originally constructed for personal use. Based on the example of Enzymolum and the algorithm for creating new enzyme biotests with tailored characteristics, a new approach was demonstrated in biotechnological design and construction. The examples of biotechnological design of various bioluminescent methods for ecological monitoring were provided. Possible applications of enzyme bioassays are seen in the examples for medical diagnostics, assessment of the effect of physical load on sportsmen, analysis of food additives, and in practical courses for higher educational institutions and schools. The advantages of enzymatic assays are their rapidity (the period of time required does not exceed 3-5 min), high sensitivity, simplicity and safety of procedure, and possibility of automation of ecological monitoring; the required luminometer is easily available.

WOS
Держатели документа:
Inst Biophys SB RAS, Krasnoyarsk 660036, Russia.
Siberian Fed Univ, Krasnoyarsk 660041, Russia.
ИБФ СО РАН

Доп.точки доступа:
Esimbekova, Elena; Kratasyuk, Valentina; Shimomura, Osamu

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11.

A study of the phenological variability of terrestrial ecosystems in the south of the Krasnoyarsk Territory and Khakassia based on satellite data / I. Y. Botvich, A. P. Shevyrnogov // Biophysics. - 2017. - Vol. 62, Is. 4. - P667-670, DOI 10.1134/S0006350917040030 . - ISSN 0006-3509
Кл.слова (ненормированные):
agricultural crops -- phenology -- satellite data -- woody vegetation
Аннотация: The patterns of the phase portraits of vegetation (agrophytocenosis, woody vegetation) constructed using two-dimensional space radiation temperature values and Normalized Difference Vegetation Index were studied. An analysis of the phenological variability of vegetation in the south of the Krasnoyarsk Territory and the Republic of Khakassia during the growing seasons of 2003 and 2006 was carried out. Distinctive features of the phase portraits of agrophytocenosis and woody vegetation were revealed. The possibility of determining the boundaries of phenological states in the phytocenosis, and the transition range from one state into another was shown. Based on the complex analysis of the reflexive and radiative properties of the plant samples, an algorithm for calculating the start and end of the growing season was developed. © 2017, Pleiades Publishing, Inc.

Scopus,
Смотреть статью
Держатели документа:
Institute of Biophysics, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Botvich, I. Y.; Shevyrnogov, A. P.

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12.

Software for matching standard activity enzyme biosensors for soil pollution analysis / V. A. Kratasyuk, E. M. Kolosova, O. S. Sutormin [et al.] // Sensors. - 2021. - Vol. 21, Is. 3. - Ст. 1017. - P1-10, DOI 10.3390/s21031017 . - ISSN 1424-8220
Кл.слова (ненормированные):
Bacterial luciferase -- Biosensors -- Butyrylcholinesterase -- Enzyme -- Lactic dehydrogenase -- Software -- Soil pollution -- Biosensors -- Soil pollution -- Soil surveys -- Soils -- Commercial standards -- Environmental Monitoring -- Enzyme biosensors -- Enzyme systems -- Inhibitory effect -- JavaScript programming -- Soil sample -- Toxic agents -- Enzyme activity
Аннотация: 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Scopus
Держатели документа:
Department of Biophysics, Institute of Fundamental Biology and Biotechology, Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation
Federal Research Center ‘Krasnoyarsk Science Center SB RAS’, Photobiology Laboratory, Institute of Biophysics, Russian Academy of Sciences, Siberian Branch, 50/50 Akagemgorodok, Krasnoyarsk, 660036, Russian Federation
Department of High-Efficiency Calculations, Siberian Federal University, 26-ULK building Kirensky St, Krasnoyarsk, 660074, Russian Federation
Federal Research Center ‘Krasnoyarsk Science Center SB RAS’, Krasnoyarsk Research Institute of Agriculture, Russian Academy of Sciences, Siberian Branch, 66 Svobodny pr, Krasnoyarsk, 660037, Russian Federation
Federal Research Center ‘Krasnoyarsk Scientific Center SB RAS’, Krasnoyarsk Research Institute of Agricultural, Siberian Federal University, 79 Svobodny pr, Krasnoyarsk, 660041, Russian Federation

Доп.точки доступа:
Kratasyuk, V. A.; Kolosova, E. M.; Sutormin, O. S.; Lonshakova-Mukina, V. I.; Baygin, M. M.; Rimatskaya, N. V.; Sukovataya, I. E.; Shpedt, A. A.

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13.

Software for Matching Standard Activity Enzyme Biosensors for Soil Pollution Analysis / V. A. Kratasyuk, E. M. Kolosova, O. S. Sutormin [et al.] // Sensors. - 2021. - Vol. 21, Is. 3. - Ст. 1017, DOI 10.3390/s21031017. - Cited References:20. - This research was funded by RFBR, Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science, Grant number 20-44-243001 and the Ministry of Science and Higher Education of the Russian Federation, Grant number FSRZ-2020-0006. . - ISSN 1424-8220

РУБ Chemistry, Analytical + Engineering, Electrical & Electronic + Instruments

Кл.слова (ненормированные):
biosensors -- enzyme -- butyrylcholinesterase -- lactic dehydrogenase -- bacterial luciferase -- soil pollution -- software
Аннотация: 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.

WOS
Держатели документа:
Siberian Fed Univ, Inst Fundamental Biol & Biotechol, Dept Biophys, 79 Svobodny Pr, Krasnoyarsk 660041, Russia.
Russian Acad Sci, Krasnoyarsk Sci Ctr SB RAS, Photobiol Lab, Fed Res Ctr,Siberian Branch,Inst Biophys, 50-50 Akagemgorodok, Krasnoyarsk 660036, Russia.
Siberian Fed Univ, Dept High Efficiency Calculat, 26 ULK Bldg Kirensky St, Krasnoyarsk 660074, Russia.
Russian Acad Sci, Krasnoyarsk Sci Ctr SB RAS, Krasnoyarsk Res Inst Agr, Siberian Branch,Fed Res Ctr, 66 Svobodny Pr, Krasnoyarsk 660037, Russia.
Siberian Fed Univ, Inst Fundamental Biol & Biotechol, Dept Aquat & Terr Ecosyst, 79 Svobodny Pr, Krasnoyarsk 660041, Russia.

Доп.точки доступа:
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.; RFBRRussian Foundation for Basic Research (RFBR); Krasnoyarsk Territory and Krasnoyarsk Regional Fund of Science [20-44-243001]; Ministry of Science and Higher Education of the Russian Federation [FSRZ-2020-0006]

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