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43,452 result(s) for "Biology Data processing."
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Biomolecular information processing
Edited by a renowned and much cited chemist, this book covers the whole span of molecular computers that are based on biomolecules. The contributions by all the major scientists in the field provide an excellent overview of the latest developments in this rapidly expanding area. A must-have for all researchers working on this very hot topic. Perfectly complements Molecular and Supramolecular Information Processing, also by Prof. Katz, and available as a two-volume set.
Collecting experiments : making Big Data biology
Databases have revolutionized nearly every aspect of our lives. Information of all sorts is being collected on a massive scale, from Google to Facebook and well beyond. But as the amount of information in databases explodes, we are forced to reassess our ideas about what knowledge is, how it is produced, to whom it belongs, and who can be credited for producing it. Every scientist working today draws on databases to produce scientific knowledge. Databases have become more common than microscopes, voltmeters, and test tubes, and the increasing amount of data has led to major changes in research practices and profound reflections on the proper professional roles of data producers, collectors, curators, and analysts. Collecting Experiments traces the development and use of data collections, especially in the experimental life sciences, from the early twentieth century to the present. It shows that the current revolution is best understood as the coming together of two older ways of knowing--collecting and experimenting, the museum and the laboratory. Ultimately, Bruno J. Strasser argues that by serving as knowledge repositories, as well as indispensable tools for producing new knowledge, these databases function as digital museums for the twenty-first century.
Bayesian population analysis using WinBUGS : a hierarchical perspective
Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS, and its open-source sister OpenBugs, is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Comprehensive and richly commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologistAll WinBUGS/OpenBUGS analyses are completely integrated in software RIncludes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R
Biomolecular networks
Alternative techniques and tools for analyzing biomolecular networks. With the recent rapid advances in molecular biology, high-throughput experimental methods have resulted in enormous amounts of data that can be used to study biomolecular networks in living organisms. With this development has come recognition of the fact that a complicated living organism cannot be fully understood by merely analyzing individual components. Rather, it is the interactions of components or biomolecular networks that are ultimately responsible for an organism's form and function. This book addresses the import
Introduction to Computer-Intensive Methods of Data Analysis in Biology
This 2006 guide to the contemporary toolbox of methods for data analysis will serve graduate students and researchers across the biological sciences. Modern computational tools, such as Maximum Likelihood, Monte Carlo and Bayesian methods, mean that data analysis no longer depends on elaborate assumptions designed to make analytical approaches tractable. These new 'computer-intensive' methods are currently not consistently available in statistical software packages and often require more detailed instructions. The purpose of this book therefore is to introduce some of the most common of these methods by providing a relatively simple description of the techniques. Examples of their application are provided throughout, using real data taken from a wide range of biological research. A series of software instructions for the statistical software package S-PLUS are provided along with problems and solutions for each chapter.
Bioinformation
\"From DNA sequences stored on computer databases to archived forensic samples and biomedical records, bioinformation comes in many forms. Its unique provenance ? the fact that it is \"mined\" from the very fabric of the human body? makes it a mercurial resource; one that no one seemingly owns, but in which many have deeply vested interests. Who has the right to exploit and benefit from bioinformation? The individual or community from whom it was derived? The scientists and technicians who make its extraction both possible and meaningful or the commercial and political interests which fund this work? Who is excluded or even at risk from its commercialisation? And what threats and opportunities might the generation of ? Big Bioinformational Data? raise? In this groundbreaking book, authors Bronwyn Parry and Beth Greenhough explore the complex economic, social and political questions arising from the creation and use of bioinformation. Drawing on a range of highly topical cases, including the commercialization of human sequence data; the forensic use of retained bioinformation; biobanking and genealogical research, they show how demand for this resource has grown significantly driving a burgeoning but often highly controversial global economy in bioinformation. But, they argue, change is afoot as new models emerge that challenge the ethos of privatisation by creating instead a dynamic open source \"bioinformational commons\" available for all future generations\"-- Provided by publisher.
Artificial Neural Networks in Biological and Environmental Analysis
Based on our knowledge of the functioning human brain, ANNs (artificial neural networks) serve as a modern paradigm for computing. Drawing on the author's substantial experience, this book provides a comprehensive introduction and practical guide to the development, optimization, and application of ANNs in modern environmental and biological analysis. Presenting basic principles together with simulated biological and environmental data sets and real applications in the field, this volume helps scientists use the power of the ANN model to explain physical concepts and to demonstrate complex natural processes.