R is quickly becoming the number one choice for users in the fields of biology, medicine, and bioinformatics as their main means of storing, processing, sharing, and analyzing biomedical data. R for Medicine and Biology is a step-by-step guide through the use of the statistical environment R, as used in a biomedical domain. Ideal for healthcare professionals, scientists, informaticists, and statistical experts, this resource will provide even the novice programmer with the tools necessary to process and analyze their data using the R environment. Introductory chapters guide readers in how to obtain, install, and become familiar with R and provide a clear introduction to the programming language using numerous worked examples. Later chapters outline how R can be used, not just for biomedical data analysis, but also as an environment for the processing, storing, reporting, and sharing of data and results. The remainder of the book explores areas of R application to common domains of biomedical informatics, including imaging, statistical analysis, data mining/modeling, pathology informatics, epidemiology, clinical trials, and metadata usage. R for Medicine and Biology will provide you with a single desk reference for the R environment and its many capabilities.

Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

In considering ways that physics has helped advance biology and medicine, what typically comes to mind are the various tools used by researchers and clinicians. We think of the optics put to work in microscopes, endoscopes, and lasers; the advanced diagnostics permitted through magnetic, x-ray, and ultrasound imaging; and even the nanotools, that a

A brilliant young scientist introduces us to the fascinating field that is changing our understanding of how the body works and the way we can approach healing. SYSTEMATIC is the first book to introduce general readers to systems biology, which is improving medical treatments and our understanding of living things. In traditional bottom-up biology, a biologist might spend years studying how a single protein works, but systems biology studies how networks of those proteins work together--how they promote health and how to remedy the situation when the system isn't functioning properly. Breakthroughs in systems biology became possible only when powerful computer technology enabled researchers to process massive amounts of data to study complete systems, and has led to progress in the study of gene regulation and inheritance, cancer drugs personalized to an individual's genetically unique tumor, insights into how the brain works, and the discovery that the bacteria and other microbes that live in the gut may drive malnutrition and obesity. Systems biology is allowing us to understand more complex phenomena than ever before. In accessible prose, SYSTEMATIC sheds light not only on how systems within the body work, but also on how research is yielding new kinds of remedies that enhance and harness the body's own defenses.

This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.

This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.

Medical Cell Biology, Third Edition, focuses on the scientific aspects of cell biology important to medical students, dental students, veterinary students, and prehealth undergraduates. With its National Board-type questions, this book is specifically designed to prepare students for this exam. The book maintains a concise focus on eukaryotic cell biology as it relates to human and animal disease, all within a manageable 300-page format. This is accomplished by explaining general cell biology principles in the context of organ systems and disease. This updated version contains 60% new material and all new clinical cases. New topics include apoptosis and cell death from a neural perspective; signal transduction as it relates to normal and abnormal heart function; and cell cycle and cell division related to cancer biology. - 60% New Material! - New Topics include: - Apoptosis and cell dealth from a neural perspective - Signal transduction as it relates to normal and abnormal heart function - Cell cycle and cell division related to cancer biology - All new clinical cases - Serves as a prep guide to the National Medical Board Exam with sample board-style questions (using Exam Master(R) technology): www.exammaster.com - Focuses on eukaryotic cell biology as it related to human disease, thus making the subject more accessible to pre-med and pre-health students