Once again, Jules J. Berman provides biomedical researchers and hospital professionals with an introduction to a time-saving programming language. In this new how-to manual, Berman expertly guides both experienced and inexperienced programmers through the Ruby programming language. Ruby Programming for Medicine and Biology opens with three chapters of Ruby language instruction followed by discussions of 100 ruby scripts covering the most common computational tasks in the field of biomedicine. With helpful explanations of how scripts work, and how they might be implemented in real-world situations, readers will become familiar with this free, open source, object-oriented programming language that is quickly gaining momentum within the bioinformatics community.

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.

Beginning with a survey of fundamental concepts associated with data integration, knowledge representation, and hypothesis generation from heterogeneous data sets, Methods in Biomedical Informatics provides a practical survey of methodologies used in biological, clinical, and public health contexts. These concepts provide the foundation for more advanced topics like information retrieval, natural language processing, Bayesian modeling, and learning classifier systems. The survey of topics then concludes with an exposition of essential methods associated with engineering, personalized medicine, and linking of genomic and clinical data. Within an overall context of the scientific method, Methods in Biomedical Informatics provides a practical coverage of topics that is specifically designed for: (1) domain experts seeking an understanding of biomedical informatics approaches for addressing specific methodological needs; or (2) biomedical informaticians seeking an approachable overview of methodologies that can be used in scenarios germane to biomedical research. - Contributors represent leading biomedical informatics experts: individuals who have demonstrated effective use of biomedical informatics methodologies in the real-world, high-quality biomedical applications - Material is presented as a balance between foundational coverage of core topics in biomedical informatics with practical "in-the-trenches" scenarios. - Contains appendices that function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4) Web Services.

Despite what you may have read in the popular press and in social media, Precision Medicine is not devoted to finding unique treatments for individuals, based on analyzing their DNA. To the contrary, the goal of Precision Medicine is to find general treatments that are highly effective for large numbers of individuals who fall into precisely diagnosed groups. We now know that every disease develops over time, through a sequence of defined biological steps, and that these steps may differ among individuals, based on genetic and environmental conditions. We are currently developing rational therapies and preventive measures, based on our precise understanding of the steps leading to the clinical expression of diseases. Precision Medicine and the Reinvention of Human Disease explains the scientific breakthroughs that have changed the way that we understand diseases, and reveals how medical scientists are using this new knowledge to launch a medical revolution. - Clarifies the foundational concepts of Precision Medicine, distinguishing this field from its predecessors such as genomics, pharmacogenetics, and personalized medicine - Gathers the chief conceptual advances in the fields of genetics, pathology, and bioinformatics, and synthesizes a coherent narrative for the field of Precision Medicine - Delivers its message in plain language, and in a relaxed, conversational writing style, making it easy to understand the complex subject matter - Guides the reader through a coherent and logical narrative, gradually providing expertise and skills along the way - Covers the importance of data sharing in Precision Medicine, and the many data-related challenges that confront this fragile new field

Written for the introductory human biology course, the Seventh Edition of Chiras' acclaimed text maintains the original organizational theme of homeostasis presented in previous editions to present the fundamental concepts of mammalian biology and human structure and function. Chiras discusses the scientific process in a thought-provoking way that asks students to become deeper, more critical thinkers. The focus on health and homeostasis allows students to learn key concepts while also assessing their own health needs. An updated and enhanced ancillary package includes numerous student and instructor tools to help students get the most out of their course!

Data Simplification: Taming Information With Open Source Tools addresses the simple fact that modern data is too big and complex to analyze in its native form. Data simplification is the process whereby large and complex data is rendered usable. Complex data must be simplified before it can be analyzed, but the process of data simplification is anything but simple, requiring a specialized set of skills and tools. This book provides data scientists from every scientific discipline with the methods and tools to simplify their data for immediate analysis or long-term storage in a form that can be readily repurposed or integrated with other data. Drawing upon years of practical experience, and using numerous examples and use cases, Jules Berman discusses the principles, methods, and tools that must be studied and mastered to achieve data simplification, open source tools, free utilities and snippets of code that can be reused and repurposed to simplify data, natural language processing and machine translation as a tool to simplify data, and data summarization and visualization and the role they play in making data useful for the end user. - Discusses data simplification principles, methods, and tools that must be studied and mastered - Provides open source tools, free utilities, and snippets of code that can be reused and repurposed to simplify data - Explains how to best utilize indexes to search, retrieve, and analyze textual data - Shows the data scientist how to apply ontologies, classifications, classes, properties, and instances to data using tried and true methods

Written for the introductory human biology course, the Seventh Edition of Chiras' acclaimed text maintains the original organizational theme of homeostasis presented in previous editions to present the fundamental concepts of mammalian biology and human structure and function. Chiras discusses the scientific process in a thought-provoking way that asks students to become deeper, more critical thinkers. The focus on health and homeostasis allows students to learn key concepts while also assessing their own health needs. An updated and enhanced ancillary package includes numerous student and instructor tools to help students get the most out of their course!