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Principles of Big Data
Principles of Big Data helps readers avoid the common mistakes that endanger all Big Data projects. By stressing simple, fundamental concepts, this book teaches readers how to organize large volumes of complex data, and how to achieve data permanence when the content of the data is constantly changing. General methods for data verification and validation, as specifically applied to Big Data resources, are stressed throughout the book. The book demonstrates how adept analysts can find relationships among data objects held in disparate Big Data resources, when the data objects are endowed with semantic support (i.e., organized in classes of uniquely identified data objects). Readers will learn...
Principles and Practice of Big Data
Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition updates and expands on the first edition, bringing a set of techniques and algorithms that are tailored to Big Data projects. The book stresses the point that most data analyses conducted on large, complex data sets can be achieved without the use of specialized suites of software (e.g., Hadoop), and without expensive hardware (e.g., supercomputers). The core of every algorithm described in the book can be implemented in a few lines of code using just about any popular programming language (Python snippets are provided). Through the use of new multiple examples, this edition demonstrate...
Biomedical Informatics
Ideal for healthcare workers, students and biomedical researchers who wish to use informatics technologies in their own clinics and laboratories, Biomedical Informatics describes the fundamental issues and questions in the field and reviews the different types of biomedical data resources and open source tools needed to fully utilize biomedical data. You are shown how to navigate through the legal, ethical, and technical hazards of biomedical informatics to become self-sufficient and productive. You will finish with an understanding of how to acquire, organize, annotate, and share biomedical data, how to render confidential data harmless through de-identification, and how to use a variety of free and open source utilities to solve common computational tasks. Berman also discusses how the Perl Language is used in biomedical informatics and provides short Perl scripts that can be applied in the biological research and healthcare settings.
Precision Medicine and the Reinvention of Human Disease
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 clinic...
Classification Made Relevant
Classification Made Relevant: How Scientists Build and Use Classifications and Ontologies explains how classifications and ontologies are designed and used to analyze scientific information. The book presents the fundamentals of classification, leading up to a description of how computer scientists use object-oriented programming languages to model classifications and ontologies. Numerous examples are chosen from the Classification of Life, the Periodic Table of the Elements, and the symmetry relationships contained within the Classification Theorem of Finite Simple Groups. When these three classifications are tied together, they provide a relational hierarchy connecting all of the natural s...
Data Simplification
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 u...
Repurposing Legacy Data
Repurposing Legacy Data: Innovative Case Studies takes a look at how data scientists have re-purposed legacy data, whether their own, or legacy data that has been donated to the public domain. Most of the data stored worldwide is legacy data—data created some time in the past, for a particular purpose, and left in obsolete formats. As with keepsakes in an attic, we retain this information thinking it may have value in the future, though we have no current use for it. The case studies in this book, from such diverse fields as cosmology, quantum physics, high-energy physics, microbiology, psychiatry, medicine, and hospital administration, all serve to demonstrate how innovative people draw v...
Logic and Critical Thinking in the Biomedical Sciences
All too often, individuals engaged in the biomedical sciences assume that numeric data must be left to the proper authorities (e.g., statisticians and data analysts) who are trained to apply sophisticated mathematical algorithms to sets of data. This is a terrible mistake. Individuals with keen observational skills, regardless of their mathematical training, are in the best position to draw correct inferences from their own data and to guide the subsequent implementation of robust, mathematical analyses. Volume 2 of Logic and Critical Thinking in the Biomedical Sciences provides readers with a repertoire of deductive non-mathematical methods that will help them draw useful inferences from th...
Logic and Critical Thinking in the Biomedical Sciences
Science is not a collection of facts. Science is the process by which we draw inferences from facts. Volume I of Logic and Critical Thinking in the Biomedical Sciences invites readers to linger over a collection of common observations to see what inferences can be drawn, when one applies a bit of deductive logic. If we just think about what we observe, it is often possible to discover profound biomedical insights.Volumes 1 and 2 of Logic and Critical Thinking in the Biomedical Sciences are written for biomedical scientists and college-level students engaged in any of the life sciences, including bioinformatics and related data sciences. Provides a strong introduction to deductive methods that can be directly applied to the biomedical sciences Using hundreds of examples, shows how creative scientists draw important inferences from observations that are often ignored by their peers Discusses complex biological and medical concepts in a relaxed manner, intended to focus the reader’s attention on the deductive process, without dwelling excessively on details
Taxonomic Guide to Infectious Diseases
As a consultant to the plastics industry, Ottmar Brandau's focus is on using his engineering knowhow and production management experience to improve quality and productivity, cut down cycle time and introduce secondary processes such as inline printing. This book is a thoroughly practical handbook which provides engineers and managers with the toolkit to improve production and engineering aspects in their own businesses - saving money, increasing output and improving competitiveness by adopting new technologies. In this book, Brandau covers the engineering aspects of bottle production and the relevant production processes (focusing on blow molding), along with plant lay-out and organization and production management, to produce the definitive handbook for engineers and managers alike. . Learn the tricks of the trade from an experienced engineer and manager . Save money: Practical strategies to improve cycle times . Increase productivity: Improve plant lay-out and organization and implement secondary processes such as inline printing.
