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58 results in Quantitative biology, biostatistics and mathematical modeling

Page 1 of 3

Experimental Design and Data Analysis for Biologists
  • 2nd edition
  • Gerry P. Quinn, Michael J. Keough
  • Published online:
    04 September 2023
    Print publication:
    07 September 2023
  • Applying statistical concepts to biological scenarios, this established textbook continues to be the go-to tool for advanced undergraduates and postgraduates studying biostatistics or experimental design in biology-related areas. Chapters cover linear models, common regression and ANOVA methods, mixed effects models, model selection, and multivariate methods used by biologists, requiring only introductory statistics and basic mathematics. Demystifying statistical concepts with clear, jargon-free explanations, this new edition takes a holistic approach to help students understand the relationship between statistics and experimental design. Each chapter contains further-reading recommendations, and worked examples from today's biological literature. All examples reflect modern settings, methodology and equipment, representing a wide range of biological research areas. These are supported by hands-on online resources including real-world data sets, full R code to help repeat analyses for all worked examples, and additional review questions and exercises for each chapter.

Applied Longitudinal Data Analysis for Medical Science
  • A Practical Guide
  • 3rd edition
  • Jos W. R. Twisk
  • Published online:
    20 April 2023
    Print publication:
    27 April 2023
  • Essential for non-statisticians and researchers working with longitudinal data from medical studies, this updated new edition discusses the most important techniques available for analysing data of this type. Using non-technical language, the book explores simple methods such as the paired t-test and summary statistics as well as more sophisticated regression-based methods, including mixed model analysis. The emphasis of the discussion lies in the interpretation of the results of these different methods, covering data analysis with continuous, dichotomous, categorical and other outcome variables. Datasets used throughout the book are provided, enabling readers to re-analyse the examples as they make their way through chapters and improve their understanding of the material. Finally, an extensive and practical overview of, and comparison between, different software packages is provided. Readers will be able to use this book as a practical manual in their everyday work without needing a strong background in statistics.

Introduction to Adaptive Trial Designs and Master Protocols
  • Jay J. H. Park, Edward J. Mills, J. Kyle Wathen
  • Published online:
    20 March 2023
    Print publication:
    06 April 2023
  • This practical high-level guidebook offers an in-depth understanding of the newly emerging clinical trial designs in adaptive trial designs and master protocols. Both concise and readable without shying away from technical discussion, the book introduces the most innovative approaches in clinical trial research such as adaptive trial designs, master protocols, platform trial, basket trial, and umbrella trial designs. Featuring a revisionist history of clinical research before moving on to case-study based discussion and practical considerations from collective experience. The book enables readers to understand the strengths and limitations of these novel designs as well as their application to individual areas of research and clinical practice. Supplemented by real-world examples from the recent developments in medical research efficiency instigated by both personalized medicine and high-profile diseases like COVID-19 and cancer. The first book of its kind, it is the go-to resource for medical students and researchers working in clinical trial research.

Statistical Hypothesis Testing in Context
  • Reproducibility, Inference, and Science
  • Volume 52
  • Michael P. Fay, Erica H. Brittain
  • Published online:
    17 April 2022
    Print publication:
    05 May 2022
  • Fay and Brittain present statistical hypothesis testing and compatible confidence intervals, focusing on application and proper interpretation. The emphasis is on equipping applied statisticians with enough tools - and advice on choosing among them - to find reasonable methods for almost any problem and enough theory to tackle new problems by modifying existing methods. After covering the basic mathematical theory and scientific principles, tests and confidence intervals are developed for specific types of data. Essential methods for applications are covered, such as general procedures for creating tests (e.g., likelihood ratio, bootstrap, permutation, testing from models), adjustments for multiple testing, clustering, stratification, causality, censoring, missing data, group sequential tests, and non-inferiority tests. New methods developed by the authors are included throughout, such as melded confidence intervals for comparing two samples and confidence intervals associated with Wilcoxon-Mann-Whitney tests and Kaplan-Meier estimates. Examples, exercises, and the R package asht support practical use.

Statistics for Laboratory Scientists and Clinicians
  • A Practical Guide
  • Anne McDonnell Sill
  • Published online:
    17 June 2021
    Print publication:
    08 July 2021
  • Understanding the underlying principles of statistical techniques and effectively applying statistical methods can be challenging for researchers at all stages of their career. This concise, practical guide uses a simple, engaging approach to take scientists and clinicians working in laboratory-based life science and medical research through the steps of choosing and implementing appropriate statistical methods to analyse results. The author draws on her extensive experience of advising students and researchers over the past 30 years, breaking down complex concepts into easy-to-understand units. Practical examples using free online statistical tools are included throughout, with illustrations and diagrams employed to keep jargon to a minimum. Sample size calculations and considerations are covered in depth, and the book refers to types of data from experiments that clinicians and lab-based scientists are likely to encounter. Straightforward, accessible and encouraging throughout, this is a go-to reference for researchers who want to achieve statistical autonomy.

Entropy and Diversity
  • The Axiomatic Approach
  • Tom Leinster
  • Published online:
    21 April 2021
    Print publication:
    22 April 2021
  • The global biodiversity crisis is one of humanity's most urgent problems, but even quantifying biological diversity is a difficult mathematical and conceptual challenge. This book brings new mathematical rigour to the ongoing debate. It was born of research in category theory, is given strength by information theory, and is fed by the ancient field of functional equations. It applies the power of the axiomatic method to a biological problem of pressing concern, but it also presents new theorems that stand up as mathematics in their own right, independently of any application. The question 'what is diversity?' has surprising mathematical depth, and this book covers a wide breadth of mathematics, from functional equations to geometric measure theory, from probability theory to number theory. Despite this range, the mathematical prerequisites are few: the main narrative thread of this book requires no more than an undergraduate course in analysis.

Biostatistics with R
  • An Introductory Guide for Field Biologists
  • Jan Lepš, Petr Šmilauer
  • Published online:
    18 September 2020
    Print publication:
    30 July 2020
  • Biostatistics with R provides a straightforward introduction on how to analyse data from the wide field of biological research, including nature protection and global change monitoring. The book is centred around traditional statistical approaches, focusing on those prevailing in research publications. The authors cover t-tests, ANOVA and regression models, but also the advanced methods of generalised linear models and classification and regression trees. Chapters usually start with several useful case examples, describing the structure of typical datasets and proposing research-related questions. All chapters are supplemented by example datasets, step-by-step R code demonstrating analytical procedures and interpretation of results. The authors also provide examples of how to appropriately describe statistical procedures and results of analyses in research papers. This accessible textbook will serve a broad audience, from students, researchers or professionals looking to improve their everyday statistical practice, to lecturers of introductory undergraduate courses. Additional resources are provided on www.cambridge.org/biostatistics.

Wildlife Disease Ecology
  • Linking Theory to Data and Application
  • Edited by Kenneth Wilson, Andy Fenton, Dan Tompkins
  • Published online:
    28 October 2019
    Print publication:
    14 November 2019
  • Just like humans, animals and plants suffer from infectious diseases, which can critically threaten biodiversity. This book describes key studies that have driven our understanding of the ecology and evolution of wildlife diseases. Each chapter introduces the host and disease, and explains how that system has aided our general understanding of the evolution and spread of wildlife diseases, through the development and testing of important epidemiological and evolutionary theories. Questions addressed include: How do hosts and parasites co-evolve? What determines how fast a disease spreads through a population? How do co-infecting parasites interact? Why do hosts vary in parasite burden? Which factors determine parasite virulence and host resistance? How do parasites influence the spread of invasive species? How do we control infectious diseases in wildlife? This book will provide a valuable introduction to students new to the topic, and novel insights to researchers, professionals and policymakers working in the field.

Cellular Biophysics and Modeling
  • A Primer on the Computational Biology of Excitable Cells
  • Greg Conradi Smith
  • Published online:
    04 March 2019
    Print publication:
    14 March 2019
  • What every neuroscientist should know about the mathematical modeling of excitable cells. Combining empirical physiology and nonlinear dynamics, this text provides an introduction to the simulation and modeling of dynamic phenomena in cell biology and neuroscience. It introduces mathematical modeling techniques alongside cellular electrophysiology. Topics include membrane transport and diffusion, the biophysics of excitable membranes, the gating of voltage and ligand-gated ion channels, intracellular calcium signalling, and electrical bursting in neurons and other excitable cell types. It introduces mathematical modeling techniques such as ordinary differential equations, phase plane, and bifurcation analysis of single-compartment neuron models. With analytical and computational problem sets, this book is suitable for life sciences majors, in biology to neuroscience, with one year of calculus, as well as graduate students looking for a primer on membrane excitability and calcium signalling.

A Course in Morphometrics for Biologists
  • Geometry and Statistics for Studies of Organismal Form
  • Fred L. Bookstein
  • Published online:
    21 September 2018
    Print publication:
    04 October 2018
  • This book builds a much-needed bridge between biostatistics and organismal biology by linking the arithmetic of statistical studies of organismal form to the biological inferences that may follow from it. It incorporates a cascade of new explanations of regression, correlation, covariance analysis, and principal components analysis, before applying these techniques to an increasingly common data resource: the description of organismal forms by sets of landmark point configurations. For each data set, multiple analyses are interpreted and compared for insight into the relation between the arithmetic of the measurements and the rhetoric of the subsequent biological explanations. The text includes examples that range broadly over growth, evolution, and disease. For graduate students and researchers alike, this book offers a unique consideration of the scientific context surrounding the analysis of form in today's biosciences.

Experimental Design for Laboratory Biologists
  • Stanley E. Lazic
  • Published online:
    28 May 2018
    Print publication:
    08 December 2016
  • Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (https://stanlazic.github.io/EDLB.html) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry.

Applying Graph Theory in Ecological Research
  • Mark R.T. Dale
  • Published online:
    31 October 2017
    Print publication:
    09 November 2017
  • Graph theory can be applied to ecological questions in many ways, and more insights can be gained by expanding the range of graph theoretical concepts applied to a specific system. But how do you know which methods might be used? And what do you do with the graph once it has been obtained? This book provides a broad introduction to the application of graph theory in different ecological systems, providing practical guidance for researchers in ecology and related fields. Readers are guided through the creation of an appropriate graph for the system being studied, including the application of spatial, spatio-temporal, and more abstract structural process graphs. Simple figures accompany the explanations to add clarity, and a broad range of ecological phenomena from many ecological systems are covered. This is the ideal book for graduate students and researchers looking to apply graph theoretical methods in their work.

Confidence, Likelihood, Probability
  • Statistical Inference with Confidence Distributions
  • Tore Schweder, Nils Lid Hjort
  • Published online:
    05 March 2016
    Print publication:
    24 February 2016
  • This lively book lays out a methodology of confidence distributions and puts them through their paces. Among other merits, they lead to optimal combinations of confidence from different sources of information, and they can make complex models amenable to objective and indeed prior-free analysis for less subjectively inclined statisticians. The generous mixture of theory, illustrations, applications and exercises is suitable for statisticians at all levels of experience, as well as for data-oriented scientists. Some confidence distributions are less dispersed than their competitors. This concept leads to a theory of risk functions and comparisons for distributions of confidence. Neyman–Pearson type theorems leading to optimal confidence are developed and richly illustrated. Exact and optimal confidence distribution is the gold standard for inferred epistemic distributions. Confidence distributions and likelihood functions are intertwined, allowing prior distributions to be made part of the likelihood. Meta-analysis in likelihood terms is developed and taken beyond traditional methods, suiting it in particular to combining information across diverse data sources.

A Biostatistics Toolbox for Data Analysis
  • Steve Selvin
  • Published online:
    05 November 2015
    Print publication:
    20 October 2015
  • This sophisticated package of statistical methods is for advanced master's (MPH) and PhD students in public health and epidemiology who are involved in the analysis of data. It makes the link from statistical theory to data analysis, focusing on the methods and data types most common in public health and related fields. Like most toolboxes, the statistical tools in this book are organized into sections with similar objectives. Unlike most toolboxes, however, these tools are accompanied by complete instructions, explanations, detailed examples, and advice on relevant issues and potential pitfalls - conveying skills, intuition, and experience. The only prerequisite is a first-year statistics course and familiarity with a computing package such as R, Stata, SPSS, or SAS. Though the book is not tied to a particular computing language, its figures and analyses were all created using R. Relevant R code, data sets, and links to public data sets are available from www.cambridge.org/9781107113084.

The Design of Mammals
  • A Scaling Approach
  • John William Prothero
  • Published online:
    05 November 2015
    Print publication:
    22 October 2015
  • Despite an astonishing 100 million-fold range in adult body mass from bumblebee bat to blue whale, all mammals are formed of the same kinds of molecules, cells, tissues and organs and to the same overall body plan. A scaling approach investigates the principles of mammal design by examining the ways in which mammals of diverse size and taxonomy are quantitatively comparable. This book presents an extensive reanalysis of scaling data collected over a quarter of a century, including many rarely or never-cited sources. The result is an unparalleled contribution to understanding scaling in mammals, addressing a uniquely extensive range of mammal attributes and using substantially larger and more rigorously screened samples than in any prior works. An invaluable resource for all those interested in the 'design' of mammals, this is an ideal resource for postgraduates and researchers in a range of fields from comparative physiology to ecology.

Systems Biology of Cancer
  • Edited by Sam Thiagalingam
  • Published online:
    05 April 2015
    Print publication:
    09 April 2015
  • With over two hundred types of cancer diagnosed to date, researchers the world over have been forced to rapidly update their understanding of the biology of cancer. In fact, only the study of the basic cellular processes, and how these are altered in cancer cells, can ultimately provide a background for rational therapies. Bringing together the state-of-the-art contributions of international experts, Systems Biology of Cancer proposes an ultimate research goal for the whole scientific community: exploiting systems biology to generate in-depth knowledge based on blueprints that are unique to each type of cancer. Readers are provided with a realistic view of what is known and what is yet to be uncovered on the aberrations in the fundamental biological processes, deregulation of major signaling networks, alterations in major cancers and the strategies for using the scientific knowledge for effective diagnosis, prognosis and drug discovery to improve public health.

Spatial Analysis
  • A Guide For Ecologists
  • 2nd edition
  • Mark R. T. Dale, Marie-Josée Fortin
  • Published online:
    05 September 2014
    Print publication:
    11 September 2014
  • Nowadays, ecologists worldwide recognize the use of spatial analysis as essential. However, because of the fast-growing range of methods available, even an expert might occasionally find it challenging to choose the most appropriate one. Providing the ecological and statistical foundations needed to make the right decision, this second edition builds and expands upon the previous one by:Encompassing the basic methods for spatial analysis, for both complete census and sample data Investigating updated treatments of spatial autocorrelation and spatio-temporal analysisIntroducing detailed explanations of currently developing approaches, including spatial and spatio-temporal graph theory, scan statistics, fibre process analysis, and Hierarchical Bayesian analysisOffering practical advice for specific circumstances, such as how to analyze forest Permanent Sample Plot data and how to proceed with transect data when portions of the data series are missing.Written for graduates, researchers and professionals, this book will be a valuable source of reference for years to come.

Multivariate Analysis of Ecological Data using CANOCO 5
  • 2nd edition
  • Petr Šmilauer, Jan Lepš
  • Published online:
    05 May 2014
    Print publication:
    17 April 2014
  • This revised and updated edition focuses on constrained ordination (RDA, CCA), variation partitioning and the use of permutation tests of statistical hypotheses about multivariate data. Both classification and modern regression methods (GLM, GAM, loess) are reviewed and species functional traits and spatial structures analysed. Nine case studies of varying difficulty help to illustrate the suggested analytical methods, using the latest version of Canoco 5. All studies utilise descriptive and manipulative approaches, and are supported by data sets and project files available from the book website: http://regent.prf.jcu.cz/maed2/. Written primarily for community ecologists needing to analyse data resulting from field observations and experiments, this book is a valuable resource to students and researchers dealing with both simple and complex ecological problems, such as the variation of biotic communities with environmental conditions or their response to experimental manipulation.

Measuring and Reasoning
  • Numerical Inference in the Sciences
  • Fred L. Bookstein
  • Published online:
    05 March 2014
    Print publication:
    28 February 2014
  • In Measuring and Reasoning, Fred L. Bookstein examines the way ordinary arithmetic and numerical patterns are translated into scientific understanding, showing how the process relies on two carefully managed forms of argument:Abduction: the generation of new hypotheses to accord with findings that were surprising on previous hypotheses, andConsilience: the confirmation of numerical pattern claims by analogous findings at other levels of measurement.These profound principles include an understanding of the role of arithmetic and, more importantly, of how numerical patterns found in one study can relate to numbers found in others. More than 200 figures and diagrams illuminate the text. The book can be read with profit by any student of the empirical nature or social sciences and by anyone concerned with how scientists persuade those of us who are not scientists why we should credit the most important claims about scientific facts or theories.

The Design and Statistical Analysis of Animal Experiments
  • Simon T. Bate, Robin A. Clark
  • Published online:
    05 March 2014
    Print publication:
    13 March 2014
  • Written for animal researchers, this book provides a comprehensive guide to the design and statistical analysis of animal experiments. It has long been recognised that the proper implementation of these techniques helps reduce the number of animals needed. By using real-life examples to make them more accessible, this book explains the statistical tools employed by practitioners. A wide range of design types are considered, including block, factorial, nested, cross-over, dose-escalation and repeated measures and techniques are introduced to analyse the experimental data generated. Each analysis technique is described in non-mathematical terms, helping readers without a statistical background to understand key techniques such as t-tests, ANOVA, repeated measures, analysis of covariance, multiple comparison tests, non-parametric and survival analysis. This is also the first text to describe technical aspects of InVivoStat, a powerful open-source software package developed by the authors to enable animal researchers to analyse their data and obtain informative results.

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