Analysis Biology
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Weighted Network Analysis
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Author : Steve Horvath
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-30
Weighted Network Analysis written by Steve Horvath and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-30 with Science categories.
High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis strategies. Gene co-expression networks have been used to study a variety of biological systems, bridging the gap from individual genes to biologically or clinically important emergent phenotypes.
Introduction To Computer Intensive Methods Of Data Analysis In Biology
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Author : Derek A. Roff
language : en
Publisher: Cambridge University Press
Release Date : 2006-05-25
Introduction To Computer Intensive Methods Of Data Analysis In Biology written by Derek A. Roff and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-25 with Medical categories.
Publisher Description
Statistical Methods In Biology
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Author : S.J. Welham
language : en
Publisher: CRC Press
Release Date : 2014-08-22
Statistical Methods In Biology written by S.J. Welham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-22 with Mathematics categories.
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.
Bioanalytics
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Author : Friedrich Lottspeich
language : en
Publisher: John Wiley & Sons
Release Date : 2018-05-29
Bioanalytics written by Friedrich Lottspeich and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-29 with Science categories.
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 bird's 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 - Protein sequence and composition analysis - DNA sequence and epigenetic modification analysis - Analysis of protein-nucleic acid interactions - Analysis of sequence data - Proteomics, metabolomics, peptidomics and toponomics - Chemical biology
Analysis Of Biological Data A Soft Computing Approach
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Author : Sanghamitra Bandyopadhyay
language : en
Publisher: World Scientific
Release Date : 2007-09-03
Analysis Of Biological Data A Soft Computing Approach written by Sanghamitra Bandyopadhyay and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-03 with Computers categories.
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.
Molecular Data Analysis Using R
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Author : Csaba Ortutay
language : en
Publisher: John Wiley & Sons
Release Date : 2017-02-06
Molecular Data Analysis Using R written by Csaba Ortutay and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-06 with Medical categories.
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.
Nonlinear Optical Polarization Analysis In Chemistry And Biology
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Author : Garth J. Simpson
language : en
Publisher: Cambridge University Press
Release Date : 2017-03-24
Nonlinear Optical Polarization Analysis In Chemistry And Biology written by Garth J. Simpson and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-24 with Mathematics categories.
Presents a clear systematic molecular-based description of nonlinear optical polarization analysis of chemical and biological assemblies.
Statistical Design And Analysis Of Biological Experiments
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Author : Hans-Michael Kaltenbach
language : en
Publisher: Springer Nature
Release Date : 2021-04-15
Statistical Design And Analysis Of Biological Experiments written by Hans-Michael Kaltenbach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-15 with Mathematics categories.
This richly illustrated book provides an overview of the design and analysis of experiments with a focus on non-clinical experiments in the life sciences, including animal research. It covers the most common aspects of experimental design such as handling multiple treatment factors and improving precision. In addition, it addresses experiments with large numbers of treatment factors and response surface methods for optimizing experimental conditions or biotechnological yields. The book emphasizes the estimation of effect sizes and the principled use of statistical arguments in the broader scientific context. It gradually transitions from classical analysis of variance to modern linear mixed models, and provides detailed information on power analysis and sample size determination, including ‘portable power’ formulas for making quick approximate calculations. In turn, detailed discussions of several real-life examples illustrate the complexities and aberrations that can arise in practice. Chiefly intended for students, teachers and researchers in the fields of experimental biology and biomedicine, the book is largely self-contained and starts with the necessary background on basic statistical concepts. The underlying ideas and necessary mathematics are gradually introduced in increasingly complex variants of a single example. Hasse diagrams serve as a powerful method for visualizing and comparing experimental designs and deriving appropriate models for their analysis. Manual calculations are provided for early examples, allowing the reader to follow the analyses in detail. More complex calculations rely on the statistical software R, but are easily transferable to other software. Though there are few prerequisites for effectively using the book, previous exposure to basic statistical ideas and the software R would be advisable.
Statistical Analysis In Biology
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Author : Kenneth Mather
language : en
Publisher:
Release Date : 1964-01-01
Statistical Analysis In Biology written by Kenneth Mather and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1964-01-01 with Biometry categories.
Computer Simulation And Data Analysis In Molecular Biology And Biophysics
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Author : Victor Bloomfield
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-06-05
Computer Simulation And Data Analysis In Molecular Biology And Biophysics written by Victor Bloomfield and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-05 with Science categories.
This book provides an introduction to two important aspects of modern bioch- istry, molecular biology, and biophysics: computer simulation and data analysis. My aim is to introduce the tools that will enable students to learn and use some f- damental methods to construct quantitative models of biological mechanisms, both deterministicandwithsomeelementsofrandomness;tolearnhowconceptsofpr- ability can help to understand important features of DNA sequences; and to apply a useful set of statistical methods to analysis of experimental data. The availability of very capable but inexpensive personal computers and software makes it possible to do such work at a much higher level, but in a much easier way, than ever before. TheExecutiveSummaryofthein?uential2003reportfromtheNationalAcademy of Sciences, “BIO 2010: Transforming Undergraduate Education for Future - search Biologists” [12], begins The interplay of the recombinant DNA, instrumentation, and digital revolutions has p- foundly transformed biological research. The con?uence of these three innovations has led to important discoveries, such as the mapping of the human genome. How biologists design, perform, and analyze experiments is changing swiftly. Biological concepts and models are becoming more quantitative, and biological research has become critically dependent on concepts and methods drawn from other scienti?c disciplines. The connections between the biological sciences and the physical sciences, mathematics, and computer science are rapidly becoming deeper and more extensive.
