Analytical Techniques in Biosciences: From basics to applications presents comprehensive and up-to-date information on the various analytical techniques obtainable in research laboratories across the biosciences. The chapters are grouped into two parts. Part I presents chapters that deals with the basic introductory protocols and sample preparatory guidelines for an error free analysis. This section also contains chapters that detail the various analytical techniques such as spectroscopy and mass spectrometry techniques, chromatographic techniques, electrophoretic techniques and molecular weight determination techniques. Part two presents chapters that capture various applied techniques in molecular biology. Techniques for nucleic acid assessments, polymerase chain reaction, DNA sequencing, enzyme application in genetic manipulation, and those used in immunology and Immunochemistry are presented as well. This book draws from experts from key institutions around the globe, who have simplified the chapters in a way that it will be useful to early-stage researchers as well as advanced scientists. The book is also carefully structured and integrated sequentially to aid flow, consistency and continuity. This is a must-have reference for graduate students and researchers in the biosciences. Presents basic analytical protocols, sample preparatory guidelines and conventional techniques in biosciences. Details the various biochemical and molecular biology techniques including spectroscopic techniques, chromatographical techniques, centrifugation techniques and titrimetric techniques. Discuses recent advances on novel techniques for screening, identification and characterization of novel molecules. Describes advanced techniques such as hyphenated techniques, electroanalytical techniques, application of biosensors in biomedical research and automated methods of analysis and robotics.
Analytical methods are the essential enabling tools of the modern biosciences. This book presents a comprehensive introduction into these analytical methods, including their physical and chemical backgrounds, as well as a discussion of the strengths and weakness of each method. It covers all major techniques for the determination and experimental analysis of biological macromolecules, including proteins, carbohydrates, lipids and nucleic acids. The presentation includes frequent cross-references in order to highlight the many connections between different techniques. The book provides a birdï¿1⁄2s eye view of the entire subject and enables the reader to select the most appropriate method for any given bioanalytical challenge. This makes the book a handy resource for students and researchers in setting up and evaluating experimental research. The depth of the analysis and the comprehensive nature of the coverage mean that there is also a great deal of new material, even for experienced experimentalists. The following techniques are covered in detail: - Purification and determination of proteins - Measuring enzymatic activity - Microcalorimetry - Immunoassays, affinity chromatography and other immunological methods - Cross-linking, cleavage, and chemical modification of proteins - Light microscopy, electron microscopy and atomic force microscopy - Chromatographic and electrophoretic techniques - Protein sequence and composition analysis - Mass spectrometry methods - Measuring protein-protein interactions - Biosensors - NMR and EPR of biomolecules - Electron microscopy and X-ray structure analysis - Carbohydrate and lipid analysis - Analysis of posttranslational modifications - Isolation and determination of nucleic acids - DNA hybridization techniques - Polymerase chain reaction techniques - DNA sequence and epigenetic modification analysis - Analysis of protein-nucleic acid interactions - Analysis of sequence data - Proteomics, metabolomics, peptidomics and toponomics - Chemical biology
|Author||: Rajan Katoch|
|Publisher||: Springer Science & Business Media|
|Release Date||: 2011-07-19|
|ISBN 10||: 9781441997852|
|Pages||: 441 pages|
Advances in biochemistry now allow us to control living systems in ways that were undreamt of a decade ago. This volume guides researchers and students through the full spectrum of experimental protocols used in biochemistry, plant biology and biotechnology.
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors’ experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. By the time you reach the end of the book (and online material) you will have gained: A clear appreciation of the importance of a statistical approach to the design of your experiments, A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables, Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly, An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working. The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.
|Author||: Keith Wilson,John Walker|
|Publisher||: Cambridge University Press|
|Release Date||: 2010-03-04|
|ISBN 10||: 1107393493|
|Pages||: 329 pages|
This best-selling undergraduate textbook provides an introduction to key experimental techniques from across the biosciences. It uniquely integrates the theories and practices that drive the fields of biology and medicine, comprehensively covering both the methods students will encounter in lab classes and those that underpin recent advances and discoveries. Its problem-solving approach continues with worked examples that set a challenge and then show students how the challenge is met. New to this edition are case studies, for example, that illustrate the relevance of the principles and techniques to the diagnosis and treatment of individual patients. Coverage is expanded to include a section on stem cells, chapters on immunochemical techniques and spectroscopy techniques, and additional chapters on drug discovery and development, and clinical biochemistry. Experimental design and the statistical analysis of data are emphasised throughout to ensure students are equipped to successfully plan their own experiments and examine the results obtained.
|Author||: Neetu Mishra,Anupam Jyoti|
|Publisher||: Bentham Science Publishers|
|Release Date||: 2019-10-30|
|ISBN 10||: 9811422850|
|Pages||: 153 pages|
Advances in biomedical research have had a profound effect on human health outcomes over the last century. Biophysical, biochemical and cellular techniques are now the backbone of modern biomedical research. Understanding these laboratory techniques is a prerequisite for investigating the processes responsible for human diseases and discovering new treatment methods. Cutting Edge Techniques in Biophysics, Biochemistry and Cell Biology: From Principle to Applications Provides information about basic and advanced analytical techniques applied in specific areas of life science and biomedical Key Features: - Book chapters present a broad overview of sophisticated analytical techniques used in biophysics, biochemistry and cell biology. - Techniques covered include in vitro cell culture techniques, flow cytometry, real time PCR, X-ray crystallography, RNA sequencing - Information about industrial and biomedical applications of techniques, (drug screening, disease models, functional assays, disease diagnosis, gene expression analysis and protein structure determination) is included. The book is an excellent introduction for students (as a textbook) and researchers (as a reference work). The information it presents will prepare readers to understand and develop research methods in life science laboratories for different projects and activities.
Biotechnology is a rapidly progressing field of science and technology. It integrates principles and applications from diverse fields such as genomics, immunology, and many more. This book strives to equip the reader with thorough knowledge about various techniques of applied biotechnology, its applications in the areas of medicine, agriculture, environment, etc., along with details about the latest equipment and analytical tools which would help the reader gain an in-depth perspective about the subject. This book elucidates new techniques and their applications in a multidisciplinary approach and is apt for students of biotechnology and associated disciplines of study.
Instrumental techniques of analysis have now moved from the confines of the chemistry laboratory to form an indispensable part of the analytical armoury of many workers involved in the biological sciences. It is now quite out of the question to considcr a laboratory dealing with the analysis of biological materials that is not equipped with an extensive range of instrumentation. Recent years have also seen a dramatic improvement in the ease with which such instruments can be used, and the quality and quantity of the analytical data that they can produce. This is due in no sm all part to the ubiquitous use of microprocessors and computers for instrumental control. However, under these circumstances there is areal danger of the analyst adopting a 'black box' mentality and not treating the analytical data produced in accordance with the limitations that may be inherent in the method used. Such a problem can only be overcome if the operator is fully aware of both the theoretical and instrumental constraints relevant to the technique in question. As the complexity and sheer volume of material in undergraduate courses increases, there is a tendency to reduce the amount of fundamental material that is taught prior to embarking on the more applied aspects. This is nowhere more apparent than in the teaching of instrumental techniques of analysis.
Basic Methods in Molecular Biology discusses the heart of the most recent revolution in biology—the development of the technology of genetics. The achievements in this field have simply changed what biologists do and, perhaps even more important, the way they think. Moreover, never before have scientists from such a broad range of disciplines rushed into such a small and slightly arcane field to learn and carry off a bit of the technology. This book comprises 21 chapters, opening with three introductory ones that discuss the basics of molecular biology; the tools of the molecular biologist; and general preparations, procedures, and considerations for use of the book. The following chapters then discuss cloning vectors and bacterial cells; preparation of DNA from eukaryotic cells; probing nucleic acids; plasmid DNA preparation; DNA restriction fragment preparation; purification of DNA; and preparation and analysis of RNA from eukaryotic cells. Other chapters cover preparation of DNA from bacteriophage clones; cloning DNA from the eukaryotic genome; subcloning into plasmids; M13 cloning and sequencing; further characterization of cloned DNA; transfection of mammalian cells in culture; protein methods; general methods; and specialized methods. This book will be of interest to practitioners in the fields of biology and molecular genetics.
|Author||: Andreas Hofmann,Samuel Clokie|
|Publisher||: Cambridge University Press|
|Release Date||: 2018-03-31|
|ISBN 10||: 1107162270|
|Pages||: 962 pages|
A major update of a best-selling textbook that introduces students to the key experimental and analytical techniques underpinning life science research.
'Analytical Techniques in Biotechnology' by Bhowmik and Bose offers a unique compendium of fundamental experiments, which forms the crucial foundation to understand this contemporary subject that has enormous impact on many other branches of life sciences. In addition to its simple and lucid language, the main focus of the book is to equip a beginner with the skill and ability required to conduct independent experimentation and research in laboratories. Carefully structured to cover the complete spectra of subjects under the umbrella of 'Biotechnology', this book is sure to prove a ready reference for students, faculties and researchers, all alike!
Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter. Sample Chapter(s). Chapter 1: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (160 KB). Contents: Overview: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (H Tang & S Kim); An Introduction to Soft Computing (A Konar & S Das); Biological Sequence and Structure Analysis: Reconstructing Phylogenies with Memetic Algorithms and Branch-and-Bound (J E Gallardo et al.); Classification of RNA Sequences with Support Vector Machines (J T L Wang & X Wu); Beyond String Algorithms: Protein Sequence Analysis Using Wavelet Transforms (A Krishnan & K-B Li); Filtering Protein Surface Motifs Using Negative Instances of Active Sites Candidates (N L Shrestha & T Ohkawa); Distill: A Machine Learning Approach to Ab Initio Protein Structure Prediction (G Pollastri et al.); In Silico Design of Ligands Using Properties of Target Active Sites (S Bandyopadhyay et al.); Gene Expression and Microarray Data Analysis: Inferring Regulations in a Genomic Network from Gene Expression Profiles (N Noman & H Iba); A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure (K Deb et al.); Feature Selection for Cancer Classification Using Ant Colony Optimization and Support Vector Machines (A Gupta et al.); Sophisticated Methods for Cancer Classification Using Microarray Data (S-B Cho & H-S Park); Multiobjective Evolutionary Approach to Fuzzy Clustering of Microarray Data (A Mukhopadhyay et al.). Readership: Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, artificial intelligence, data mining, machine learning, electrical engineering, system science; researchers in pharmaceutical industries.