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This unique text is devoted to the full range of neoplastic properties exhibited by the comprehensive collection of human neoplasms. Like no other book of it's kind, it approaches cancer biology by surveying the diversity of neoplasms and by building a classification of neoplasms based on an understanding of the cellular options for tumor development. By grouping neoplasms into a comprehensive classification, we can develop class-specific methods to prevent, detect, and treat cancers. The book is divided into three broad units: speciation, classification and eradication. In the process of developing a classification for neoplasms, dozens of the fundamental questions in neoplastic development are asked and answered. Neoplasms provides readers with a fascinating and enjoyable way to learn the otherwise arcane and dense subject of human tumor diversity.
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
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 demonstrates that if we understand our data, and if we know how to ask the right questions, we can learn a great deal from large and complex data collections. The book will assist students and professionals from all scientific backgrounds who are interested in stepping outside the traditional boundaries of their chosen academic disciplines. - Presents new methodologies that are widely applicable to just about any project involving large and complex datasets - Offers readers informative new case studies across a range scientific and engineering disciplines - Provides insights into semantics, identification, de-identification, vulnerabilities and regulatory/legal issues - Utilizes a combination of pseudocode and very short snippets of Python code to show readers how they may develop their own projects without downloading or learning new software
Evolution's Clinical Guidebook: Translating Ancient Genes into Precision Medicine demonstrates, through well-documented examples, how an understanding of the phylogenetic ancestry of humans allows us to make sense out of the flood of genetic data streaming from modern laboratories and how it can lead us to new ways to prevent, diagnose and treat diseases. Topics cover evolution and human genome, meiosis and other recombinants events, embryology, speciation, phylogeny, rare and common diseases, and the evolution of aging. This book is a valuable source for bioinformaticians and those in the biomedical field who need knowledge, down to gene level, to fully comprehend currently available data. - Offers an innovative approach, focusing on how disease-associated pathways evolved - Explains how the fields of phylogeny and embryology have become closely tied to the fields of genetics and bioinformatics - Demonstrates how students and biomedical professionals can apply the knowledge obtained in this book to the theory and practice of precision medicine
Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implemented with open source programming languages, you can fully utilize the medical information contained in clini
Rare Diseases and Orphan Drugs shows that much of what we now know about common diseases has been achieved by studying rare diseases. It proposes that future advances in the prevention, diagnosis, and treatment of common diseases will come as a consequence of our accelerating progress in the field of rare diseases. Understanding the complex steps in the development of common diseases, such as cancer, cardiovascular disease, and metabolic diseases, has proven a difficult problem. Rare diseases, however, are often caused by aberrations of a single gene. In rare diseases, we may study how specific genetic defects can trigger a series of events that lead to the expression of a particular disease. Often, the disease process manifested in a certain rare disease is strikingly similar to the disease process observed in a common disease. This work ties the lessons learned about rare diseases to our understanding of common ones. Chapters covering the number of common diseases are minimized, while rare diseases are introduced as single diseases or as members of diseases classes. After reading this book, readers will appreciate how further research into the rare diseases may lead to new methods for preventing, diagnosing, and treating all diseases, rare or common. - Makes rare diseases relevant to clinicians and researchers by tying lessons learned about the rare diseases to our understanding of the common diseases - Stresses basic pathologic mechanisms that account for human disease (e.g., disorders of cell development, replication, maintenance, function and structure), that can be understood without prior training in pathology - Discusses advanced concepts in molecular biology and genetics in a simple, functional context appropriate for medical trainees and new researchers - Offers insights into how further research into rare diseases may lead to new methods for preventing, diagnosing, and treating all diseases
Nearly every type of cancer passes through a precancer phase, during which it cannot metastasize or invade other tissues. While medicine is not always successful in treating or curing advanced stages of cancers, recent advances in our understanding of carcinogenesis have helped us to develop strategies to prevent, diagnose, and treat many cancers at the precancer stage. Research in this field is escalating rapidly as the evidence increasingly shows that the number of annual cancer deaths could be drastically reduced through the effective treatment and cure of precancer lesions. This book begins by explaining why it has been so difficult to cure cancers, followed by a review of precancer biology, with descriptions of the most common precancer lesions. The final chapters provide practical socio-political and medical goals for precancer treatment, including discussions of the economics and politics of treating precancers.
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 sciences. The book's chapters introduce and describe general concepts that can be understood by any intelligent reader. With each new concept, they follow practical examples selected from various scientific disciplines. In these cases, technical points and specialized vocabulary are linked to glossary items where the item is clarified and expanded. - Explains the theory and practice of classification, emphasizing the importance of classifications and ontologies to the modern fields of mathematics, physics, chemistry, biology and medicine - Includes numerous real-world examples that demonstrate how bad construction technique can destroy the value of classifications and ontologies - Explains how we define and understand the relationships among the classes within a classification and how the properties of a class are inherited by its subclasses - Describes ontologies and how they differ from classifications and explains conditions under which ontologies are useful
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
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