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.

This newly designed and enlarged edition offers an up-to-date presentation of biosensor development and modeling from both a chemical and a mathematical point of view. An entire new chapter in particular is dedicated to optimal design of biosensors. Two more new chapters discuss biosensors which utilize microbial cells and are based on carbon nanotubes respectively. All the other chapters have been revised and updated. The book contains unique modeling methods for amperometric, potentiometric and optical biosensors based mainly on biocatalysts . It examines processes that occur in the sensors' layers and at their interface, and it provides analytical and numerical methods to solve equations of conjugated enzymatic (chemical) and diffusion processes. The action of single enzyme as well as polyenzyme biosensors and biosensors based on chemically modified electrodes is studied. The modeling of biosensors that contain perforated membranes and multipart mass transport profiles is critically investigated. Furthermore, it is fully described how signals can be biochemically amplified, how cascades of enzymatic substrate conversion are triggered, and how signals are processed via a chemometric approach and artificial neuronal networks. The results of digital modeling are compared with both proximal analytical solutions and experimental data.

A biosensor is a detecting device that combines a transducer with a biologically sensitive and selective component. Biosensors can measure compounds present in the environment, chemical processes, food and human body at low cost if compared with traditional analytical techniques. This book covers a wide range of aspects and issues related to biosensor technology, bringing together researchers from 12 different countries. The book consists of 20 chapters written by 69 authors and divided in three sections: Biosensors Technology and Materials, Biosensors for Health and Biosensors for Environment and Biosecurity.

This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

Many researchers and research groups around the globe are dealing with interdisciplinary problems and multidisciplinary groups; but especially those that deal everyday with biosensors have the feeling of not having enough personnel with the sufficient background to cover all topics. With this feeling in our minds, we decided to invite wonderful researchers from different parts to design this book, not as a conventional biosensor’s book, but as an interesting journey in the complex world of biosensors. A close look to some recent and key advances on the topic, but at the same time tips through novel mathematical modelling to improve our work, and last but not least, tricks to fool those undesired electrical disturbances that commonly messes our daily work can be found in these pages. Feel free to navigate the book through its chapters, once in your hands you will feel eager to learn more about biosensors. It has been an experience to put all this together; but now, with the book ready, we can say that this trip has being a wonderful adventure. That is why want to thank all the authors for their great contributions, the Editorial and Irene for their constant input, and to you, the reader, for being part of this book.

This book on modelling and simulation in biomathematics will be invaluable to researchers who are interested in the emerging areas of the field. Graduate students in related areas as well as lecturers will also find it beneficial. Some of the chapters have been written by distinguished experts in the field. Sample Chapter(s). Chapter 1: Detecting Mosaic Structures in DNA Sequence Alignments (1,349 KB). Contents: Detecting Mosaic Structures in DNA Sequence Alignments (D Husmeier); Application of Statistical Methodology and Model Design to Socio-Behaviour of HIV Transmission (J Oluwoye); A Stochastic Model Incorporating HIV Treatments for a Heterosexual Population: Impact on Threshold Conditions (R J Gallop et al.); Modeling and Identification of the Dynamics of the MF-Influenced Free-Radical Transformations in Lipid-Modeling Substances and Lipids (J Bentsman et al.); Computer Simulation of Self-Reorganization in Biological Cells (D Greenspan); Modelling Biological Gel Contraction by Cells: Consequences of Cell Traction Forces Distribution and Initial Stress (S Ramtani); Peristaltic Transport of Physiological Fluids (J C Misra & S K Pandey); Mathematical Modelling of DNA Knots and Links (J C Misra & S Mukherjee); Using Monodomain Computer Models for the Simulation of Electric Fields During Excitation Spread in Cardiac Tissue (G Plank); Flow in Tubes with Complicated Geometries with Special Application to Blood Flow in Large Arteries (G Jayaraman); Mathematical Modeling in Reproductive Biomedicine (S Sharma & S K Guha); Image Theory and Applications in Bioelectromagnetics (P D Einziger et al.); Dynamics of Humanoid Robots: Geometrical and Topological Duality (V G Ivancevic); The Effects of Body Composition on Energy Expenditure and Weight Dynamics During Hypophagia: A Setpoint Analysis (F P Kozusko); Mathematical Models in Population Dynamics and Ecology (R Diluo); Modelling in Bone Biomechanics (J C Misra & S Samanta). Readership: Graduate students, academic and researchers in biomathematics, mathematical biology, mathematical modeling, biotechnology, biocomputing, biophysics, bioengineering and mechanics."

Key features include: Self-assessment questions and exercises Chapters start with essential principles, then go on to address more advanced topics More than 1300 references to direct the reader to key literature and further reading Highly illustrated with 450 figures, including chemical structures and reactions, functioning principles, constructive details and response characteristics Chemical sensors are self-contained analytical devices that provide real-time information on chemical composition. A chemical sensor integrates two distinct functions: recognition and transduction. Such devices are widely used for a variety of applications, including clinical analysis, environment monitoring and monitoring of industrial processes. This text provides an up-to-date survey of chemical sensor science and technology, with a good balance between classical aspects and contemporary trends. Topics covered include: Structure and properties of recognition materials and reagents, including synthetic, biological and biomimetic materials, microorganisms and whole-cells Physicochemical basis of various transduction methods (electrical, thermal, electrochemical, optical, mechanical and acoustic wave-based) Auxiliary materials used e.g. synthetic and natural polymers, inorganic materials, semiconductors, carbon and metallic materials properties and applications of advanced materials (particularly nanomaterials) in the production of chemical sensors and biosensors Advanced manufacturing methods Sensors obtained by combining particular transduction and recognition methods Mathematical modeling of chemical sensor processes Suitable as a textbook for graduate and final year undergraduate students, and also for researchers in chemistry, biology, physics, physiology, pharmacology and electronic engineering, this bookis valuable to anyone interested in the field of chemical sensors and biosensors.