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Biosensors are analytical devices in which speci?c recognition of the chemical substances is performed by biological material. The biological material that serves as recognition element is used in combination with a transducer. The transducer transforms concentration of substrate or product to electrical signal that is amp- ?ed and further processed. The biosensors may utilize enzymes, antibodies, nucleic acids, organelles, plant and animal tissue, whole organism or organs. Biosensors containing biological catalysts (enzymes) are called catalytical biosensors. These type of biosensors are the most abundant, and they found the largest application in medicine, ecology, and environmental monitoring. The action of catalytical biosensors is associated with substrate diffusion into biocatalytical membrane and it conversion to a product. The modeling of bios- sors involves solving the diffusion equations for substrate and product with a term containing a rate of biocatalytical transformation of substrate. The complications of modeling arise due to solving of partially differential equations with non-linear biocatalytical term and with complex boundary and initial conditions. The book starts with the modeling biosensors by analytical solution of partial differential equations. Historically this method was used to describe fundamental features of biosensors action though it is limited by substrate concentration, and is applicable for simple biocatalytical processes. Using this method the action of biosensors was analyzed at critical concentrations of substrate and enzyme activity.
List of contents
Analytical Modeling of Biosensors.- Biosensor Action.- Modeling Biosensors at Steady State and Internal Diffusion Limitations.- Modeling Biosensors at Steady State and External Diffusion Limitations.- Modeling Biosensors Utilizing Microbial Cells.- Modeling Nonstationary State of Biosensors.- Numerical Modeling of Biosensors.- Mono-Layer Mono-Enzyme Models of Biosensors.- One-Layer Multi-Enzyme Models of Biosensors.- Multi-Layer Models of Biosensors.- Modeling Biosensors of Complex Geometry.- Numerical Methods for Reaction-Diffusion Equations.- The Difference Schemes for the Diffusion Equation.- The Difference Schemes for the Reaction-Diffusion Equations.
About the author
Romas Baronas he is a Professor at the Institute of Computer Science of the Vilnius University (Lithuania) since 2005, and his main research interests cover computational modeling of nonlinear phenomena in life sciences. He received his Ph.D. in Computer Science at the same university in 2000, and from 2006 to 2017 he headed the Department of Software Engineering at the Vilnius University. He was the director of the Institute of Computer Science in 2018-2019, and as of 2019, he also works as the chairman of the Research Council of Lithuania. In 2012 he was awarded the Lithuanian Science Prize.
Feliksas Ivanauskas is a Professor Emeritus of the Vilnius University (Lithuania). He joint this university in 1972 as Senior Lecturer, and later on, as Associate Professor, Professor, Head of the Department of Mathematical Software, Head of the Department of Differential Equations and Numerical Mathematics, Head of the Department of Computer Science II, and Dean ofFaculty of Mathematics and Informatics.
He received his Ph.D. in Mathematics from the Moscow State University and the second degree (Habilitation Doctor) in Mathematics from the Institute of Mathematical Modeling, Russia AS (Moscow), in 1974 and 1992, respectively. He has published 250+ scientific articles and holds two patents on solid-state sources of light. Prof. Ivanauskas received the Lithuanian National Prizes in Science 1995 and 2010. He was Chair of the Division of Mathematical, Physical and Chemical Sciences of Lithuanian Academy of Science from 2009 until 2017.
Juozas Kulys is a Professor Emeritus of the Life Sciences Center of Vilnius University (Lithuania), and his main scientific interests focus on chemical problems of biocatalysis, biosensors development and modeling. He received his Ph.D. from the M. V. Lomonosov Moscow State University (Russia) in 1970, and the second degree (Habilitation Doctor) at the N. N. Semenov Chemical Physics Institute in1982. In 1984 he was assessed as Professor of Physical Chemistry, and worked as Senior Research Associate, Head of the Department of Enzyme Chemistry (1974-2016) and as a Director (1986-1992) of the Institute of Biochemistry of Vilnius University (Lithuania). From 2001 until 2018 he was also the Head of the Department and professor of Chemistry and Bioengineering of Vilnius Gediminas Technical University (Lithuania). He was awarded the State Science Prize (1987), the Baltic Assembly Premium of Science (1995), National Science Premium (2002), and he was elected as a member of the Lithuania Academy of Sciences (1990).
Summary
Biosensors are analytical devices in which speci?c recognition of the chemical substances is performed by biological material. The biological material that serves as recognition element is used in combination with a transducer. The transducer transforms concentration of substrate or product to electrical signal that is amp- ?ed and further processed. The biosensors may utilize enzymes, antibodies, nucleic acids, organelles, plant and animal tissue, whole organism or organs. Biosensors containing biological catalysts (enzymes) are called catalytical biosensors. These type of biosensors are the most abundant, and they found the largest application in medicine, ecology, and environmental monitoring. The action of catalytical biosensors is associated with substrate diffusion into biocatalytical membrane and it conversion to a product. The modeling of bios- sors involves solving the diffusion equations for substrate and product with a term containing a rate of biocatalytical transformation of substrate. The complications of modeling arise due to solving of partially differential equations with non-linear biocatalytical term and with complex boundary and initial conditions. The book starts with the modeling biosensors by analytical solution of partial differential equations. Historically this method was used to describe fundamental features of biosensors action though it is limited by substrate concentration, and is applicable for simple biocatalytical processes. Using this method the action of biosensors was analyzed at critical concentrations of substrate and enzyme activity.
