Download or read book Handbook of Statistical Systems Biology written by Michael Stumpf and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.
Download or read book Handbook of Statistical Bioinformatics written by Henry Horng-Shing Lu and published by Springer Nature. This book was released on 2022-12-08 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology. The three parts of the book cover statistical methods for single-cell analysis, network analysis, and systems biology, with contributions by leading experts addressing key topics in probabilistic and statistical modeling and the analysis of massive data sets generated by modern biotechnology. This handbook will serve as a useful reference source for students, researchers and practitioners in statistics, computer science and biological and biomedical research, who are interested in the latest developments in computational statistics as applied to computational biology.
Download or read book Applied Statistics for Network Biology written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2011-04-08 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems biology, researchers are trying to analyze as many data as possible in a given biological system (such as a cell or an organ). The appropriate statistical evaluation of these large scale data is critical for the correct interpretation and different experimental approaches require different approaches for the statistical analysis of these data. This book is written by biostatisticians and mathematicians but aimed as a valuable guide for the experimental researcher as well computational biologists who often lack an appropriate background in statistical analysis.
Download or read book Handbook of Systems Biology written by Marian Walhout and published by Academic Press. This book was released on 2012-12-31 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an entry point into Systems Biology for researchers in genetics, molecular biology, cell biology, microbiology and biomedical science to understand the key concepts to expanding their work. Chapters organized around broader themes of Organelles and Organisms, Systems Properties of Biological Processes, Cellular Networks, and Systems Biology and Disease discuss the development of concepts, the current applications, and the future prospects. Emphasis is placed on concepts and insights into the multi-disciplinary nature of the field as well as the importance of systems biology in human biological research. Technology, being an extremely important aspect of scientific progress overall, and in the creation of new fields in particular, is discussed in 'boxes' within each chapter to relate to appropriate topics. 2013 Honorable Mention for Single Volume Reference in Science from the Association of American Publishers' PROSE Awards Emphasizes the interdisciplinary nature of systems biology with contributions from leaders in a variety of disciplines Includes the latest research developments in human and animal models to assist with translational research Presents biological and computational aspects of the science side-by-side to facilitate collaboration between computational and biological researchers
Download or read book Handbook of Computational Molecular Biology written by Srinivas Aluru and published by CRC Press. This book was released on 2005-12-21 with total page 1108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of
Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Ken Yale and published by Elsevier. This book was released on 2017-11-09 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Download or read book Statistical Methods in Bioinformatics written by Warren J. Ewens and published by Springer Science & Business Media. This book was released on 2005-09-30 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
Download or read book Handbook of Statistical Genomics written by David J. Balding and published by John Wiley & Sons. This book was released on 2019-07-09 with total page 1828 pages. Available in PDF, EPUB and Kindle. Book excerpt: A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Download or read book Statistical Modeling and Machine Learning for Molecular Biology written by Alan Moses and published by CRC Press. This book was released on 2017-01-06 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.
Download or read book Statistical Genomics written by Ben Hui Liu and published by CRC Press. This book was released on 2017-11-22 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomics, the mapping of the entire genetic complement of an organism, is the new frontier in biology. This handbook on the statistical issues of genomics covers current methods and the tried-and-true classical approaches.
Download or read book Handbook of Computational Finance written by Jin-Chuan Duan and published by Springer Science & Business Media. This book was released on 2011-10-25 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: Any financial asset that is openly traded has a market price. Except for extreme market conditions, market price may be more or less than a “fair” value. Fair value is likely to be some complicated function of the current intrinsic value of tangible or intangible assets underlying the claim and our assessment of the characteristics of the underlying assets with respect to the expected rate of growth, future dividends, volatility, and other relevant market factors. Some of these factors that affect the price can be measured at the time of a transaction with reasonably high accuracy. Most factors, however, relate to expectations about the future and to subjective issues, such as current management, corporate policies and market environment, that could affect the future financial performance of the underlying assets. Models are thus needed to describe the stochastic factors and environment, and their implementations inevitably require computational finance tools.
Download or read book Analyzing Medical Data Using S PLUS written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each chapter consists of basic statistical theory, simple examples of S-PLUS code, plus more complex examples of S-PLUS code, and exercises. All data sets are taken from genuine medical investigations and will be available on a web site. The examples in the book contain extensive graphical analysis to highlight one of the prime features of S-PLUS. Written with few details of S-PLUS and less technical descriptions, the book concentrates solely on medical data sets, demonstrating the flexibility of S-PLUS and its huge advantages, particularly for applied medical statisticians.
Download or read book Handbook of Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2023-10-16 with total page 937 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Download or read book Computational Biology written by Scott T. Kelley and published by John Wiley & Sons. This book was released on 2018-01-01 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is for anyone who needs to learn the basics of bioinformatics—the use of computational methods to better understand biological systems. Computational Biology covers the principles and applications of the computational methods used to study DNA, RNA, and proteins, including using biological databases such as NCBI and UniProt; performing BLAST, sequence alignments, and structural predictions; and creating phylogenetic trees. It includes a primer that can be used as a jumping off point for learning computer programming for bioinformatics. This text can be used as a self-study guide, as a course focused on computational methods in biology/bioinformatics, or to supplement general courses that touch on topics included within the book. Computational Biology's robust interactive online components “gamify” the study of bioinformatics, allowing the reader to practice randomly generated problems on their own time to build confidence and skill and gain practical real-world experience. The online component also assures that the content being taught is up to date and accurately reflects the ever-changing landscape of bioinformatics web-based programs.
Download or read book Handbook of Design and Analysis of Experiments written by Angela Dean and published by CRC Press. This book was released on 2015-06-26 with total page 946 pages. Available in PDF, EPUB and Kindle. Book excerpt: This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.
Download or read book Handbook of Statistics for Teaching and Research in Plant and Crop Science written by Usha Palaniswamy and published by CRC Press. This book was released on 2005-12-08 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than a textbook—it’s also a valuable reference book for researchers and crop science professionals! The Handbook of Statistics for Teaching and Research in Plant and Crop Science presents the fundamental concepts of important statistical methods and experimental designs to the students and researchers who need to apply them to their own specific problems. This comprehensive handbook takes what can be the difficult and confusing topics of statistics and experimental design and explains them in easily understandable terms, making them accessible to nearly every reader. More than a student textbook, it is an essential reference for researchers and professionals in a multitude of fields. Designed as a two-semester statistical textbook, the first section of the Handbook of Statistics for Teaching and Research in Plant and Crop Science focuses on statistical concepts, providing a foundation of useful knowledge on which you can base your own research. The second section concentrates on experimental designs in plant and crop sciences. The material is presented in a way that helps readers with a minimum of mathematical background to understand important theories and concepts. Derivations of formulas are avoided, and mathematical symbols are used only when essential. To illustrate the computational procedures, data is drawn from actual experiments. At the end of each chapter, examples and exercises are given to provide clear insight into real-life problems. A comprehensive appendix of clearly presented statistical tables is included. Part One of Handbook of Statistics for Teaching and Research in Plant and Crop Science focuses on statistical methods, principles, and procedures, exploring: methods of display of statistical information, such as tables, diagrams, graphs, etc. symbols and their use in denoting variables descriptions of types of statistical data methods of computation from raw and graphed data the importance of studying variables and dispersion in research the use of normal probability integral tables and their application to practical problems descriptions of different types of experiments, such as determinate and nondeterminate the significance of expected value in research special techniques in descriptive statistics explanations of population, sample, and statistical inference the significance of null hypothesis in research methods of correlation studies assumptions and principles in regression analysis Part Two concentrates on experimental design, principles and procedures, exploring: basic principles of experimental design the fundamental concepts of linear models and analysis of variance method and layout of Completely Randomized Design (CRD) the advantages and disadvantages of Randomized Complete Block Design (RCBD) methods and procedures for comparison of several treatment means the important features of Latin Square Design factorial experiments split plot design completely confounded design analysis of covariance the Chi Square Test of Significance the transformation of experimental data quality control and so much more! The Handbook of Statistics for Teaching and Research in Plant and Crop Science serves not only as a textbook for instructors and students in experimental design and statistics but also as a reference book on plant and crop sciences for professionals and researchers. The comprehensive text is also useful for professionals in other statistic-heavy fields.
Download or read book The Oxford Handbook of Economics and Human Biology written by John Komlos and published by Oxford University Press. This book was released on 2016 with total page 849 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of Economics and Human Biology provides an extensive and insightful overview of how economic conditions affect human well-being and how human health influences economic outcomes. The book addresses both macro and micro factors, as well as their interaction, providing new understanding of complex relationships and developments in economic history and economic dynamics. Among the topics explored is how variation in height, whether over time, among different socioeconomic groups, or in different locations, is an important indicator of changes in economic growth and economic development, levels of economic inequality, and economic opportunities for individuals.
