Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
745
result(s) for
"Biometry Data processing."
Sort by:
Statistical Learning for Biomedical Data
This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, support vector machines, nearest neighbors and boosting.
eBook
Networks of networks in biology : concepts, tools and applications
Biological systems are extremely complex and have emergent properties that cannot be explained or even predicted by studying their individual parts in isolation. The reductionist approach, although successful in the early days of molecular biology, underestimates this complexity. As the amount of available data grows, so it will become increasingly important to be able to analyse and integrate these large data sets. This book introduces novel approaches and solutions to the Big Data problem in biomedicine, and presents new techniques in the field of graph theory for handling and processing multi-type large data sets. By discussing cutting-edge problems and techniques, researchers from a wide range of fields will be able to gain insights for exploiting big heterogonous data in the life sciences through the concept of 'network of networks'.
BOOK
Introduction to WinBUGS for ecologists : A Bayesian approach to regression, ANOVA, mixed models and related analyses
Introduction to WinBUGS for Ecologists introduces applied Bayesian modeling to ecologists using the highly acclaimed, free WinBUGS software.It offers an understanding of statistical models as abstract representations of the various processes that give rise to a data set.
eBook
Computational ecology
Graphs, networks and agent-based modeling are the most thriving and attracting sciences used in ecology and environmental sciences. As such, this book is the first comprehensive treatment of the subject in the areas of ecology and environmental sciences.
eBook
Information theory and evolution
Information Theory and Evolution discusses the phenomenon of life, including its origin and evolution (and also human cultural evolution), against the background of thermodynamics, statistical mechanics, and information theory. Among the central themes is the seeming contradiction between the second law of thermodynamics and the high degree of order and complexity produced by living systems. This paradox has its resolution in the information content of the Gibbs free energy that enters the biosphere from outside sources, as the author will show. The role of information in human cultural evolution is another focus of the book.
eBook
Understanding statistical error
This accessible introductory textbook provides a straightforward, practical explanation of how statistical analysis and error measurements should be applied in biological research.
Understanding Statistical Error - A Primer for Biologists:
* Introduces the essential topic of error analysis to biologists
* Contains mathematics at a level that all biologists can grasp
* Presents the formulas required to calculate each confidence interval for use in practice
* Is based on a successful series of lectures from the author's established course
Assuming no prior knowledge of statistics, this book covers the central topics needed for efficient data analysis, ranging from probability distributions, statistical estimators, confidence intervals, error propagation and uncertainties in linear regression, to advice on how to use error bars in graphs properly. Using simple mathematics, all these topics are carefully explained and illustrated with figures and worked examples. The emphasis throughout is on visual representation and on helping the reader to approach the analysis of experimental data with confidence.
This useful guide explains how to evaluate uncertainties of key parameters, such as the mean, median, proportion and correlation coefficient. Crucially, the reader will also learn why confidence intervals are important and how they compare against other measures of uncertainty.
Understanding Statistical Error - A Primer for Biologists can be used both by students and researchers to deepen their knowledge and find practical formulae to carry out error analysis calculations. It is a valuable guide for students, experimental biologists and professional researchers in biology, biostatistics, computational biology, cell and molecular biology, ecology, biological chemistry, drug discovery, biophysics, as well as wider subjects within life sciences and any field where error analysis is required.
eBook
Biostatistics
This book translates biostatistics in the health sciences literature with clarity and irreverence. Students and practitioners alike applaud Biostatistics: as the practical guide that exposes them to every statistical test they may encounter, with careful conceptual explanations and a minimum of algebra. The new Bare Essentials reflects recent advances in statistics, as well as time-honored methods. For example hierarchical linear modeling, which first appeared in psychology journals and only now is seen in medical literature, is described. Also new is a chapter on testing for equivalence and non-inferiority, and another on getting started with the computer statistics program, SPSS. Free of calculations and jargon, Bare Essentials speak so plainly that you won t need a technical dictionary. No math, all concepts. The objective is to enable you to determine if the research results are applicable to your own patients. Throughout the guide, you ll find highlights of areas in which researchers misuse or misinterpret statistical tests. We have labeled these C.R.A.P. Detectors (Convoluted Reasoning and Anti-intellectual Pomposity), which help you to identify faulty methodology and misuse of statistics.
eBook
Unimodal and Multimodal Biometric Data Indexing
This work is on biometric data indexing for large-scale identification systems with a focus on different biometrics data indexing methods. It provides state-of-the-art coverage including different biometric traits, together with the pros and cons for each. Discussion of different multimodal fusion strategies are also included.
eBook