Author: David Eugene Wilkins
Publisher: University of Oklahoma Press
ISBN: 9780806133959
Category : Social Science
Languages : en
Pages : 340
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Book Description
In the early 1970s, the federal government began recognizing self-determination for American Indian nations. As sovereign entities, Indian nations have been able to establish policies concerning health care, education, religious freedom, law enforcement, gaming, and taxation. David E. Wilkins and K. Tsianina Lomawaima discuss how the political rights and sovereign status of Indian nations have variously been respected, ignored, terminated, and unilaterally modified by federal lawmakers as a result of the ambivalent political and legal status of tribes under western law.
Author: Kevin Davies
Publisher: Simon and Schuster
ISBN: 1416569618
Category : Medical
Languages : en
Pages : 352
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Book Description
In 2000, President Bill Clinton signaled the completion of the Human Genome Project at a cost in excess of $2 billion. A decade later, the price for any of us to order our own personal genome sequence--a comprehensive map of the 3 billion letters in our DNA--is rapidly and inevitably dropping to just $1,000. Dozens of men and women--scientists, entrepreneurs, celebrities, and patients--have already been sequenced, pioneers in a bold new era of personalized genomic medicine. The $1,000 genome has long been considered the tipping point that would open the floodgates to this revolution. Do you have gene variants associated with Alzheimer's or diabetes, heart disease or cancer? Which drugs should you consider taking for various diseases, and at what dosage? In the years to come, doctors will likely be able to tackle all of these questions--and many more--by using a computer in their offices to call up your unique genome sequence, which will become as much a part of your medical record as your blood pressure.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309680948
Category : Medical
Languages : en
Pages : 111
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Book Description
In December 2019, new cases of severe pneumonia were first detected in Wuhan, China, and the cause was determined to be a novel beta coronavirus related to the severe acute respiratory syndrome (SARS) coronavirus that emerged from a bat reservoir in 2002. Within six months, this new virusâ€"SARS coronavirus 2 (SARS-CoV-2)â€"has spread worldwide, infecting at least 10 million people with an estimated 500,000 deaths. COVID-19, the disease caused by SARS-CoV-2, was declared a public health emergency of international concern on January 30, 2020 by the World Health Organization (WHO) and a pandemic on March 11, 2020. To date, there is no approved effective treatment or vaccine for COVID-19, and it continues to spread in many countries. Genomic Epidemiology Data Infrastructure Needs for SARS-CoV-2: Modernizing Pandemic Response Strategies lays out a framework to define and describe the data needs for a system to track and correlate viral genome sequences with clinical and epidemiological data. Such a system would help ensure the integration of data on viral evolution with detection, diagnostic, and countermeasure efforts. This report also explores data collection mechanisms to ensure a representative global sample set of all relevant extant sequences and considers challenges and opportunities for coordination across existing domestic, global, and regional data sources.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309316324
Category : Medical
Languages : en
Pages : 236
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Book Description
Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
Author: Xiaoqian Jiang
Publisher: Academic Press
ISBN: 9780128161975
Category : Science
Languages : en
Pages : 0
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Book Description
Responsible Genomic Data Sharing: Challenges and Approaches brings together international experts in genomics research, bioinformatics and digital security who analyze common challenges in genomic data sharing, privacy preserving technologies, and best practices for large-scale genomic data sharing. Practical case studies, including the Global Alliance for Genomics and Health, the Beacon Network, and the Matchmaker Exchange, are discussed in-depth, illuminating pathways forward for new genomic data sharing efforts across research and clinical practice, industry and academia.
Author: James Shreeve
Publisher: Ballantine Books
ISBN: 0307417069
Category : Science
Languages : en
Pages : 418
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Book Description
The long-awaited story of the science, the business, the politics, the intrigue behind the scenes of the most ferocious competition in the history of modern science—the race to map the human genome. On May 10, 1998, biologist Craig Venter, director of the Institute for Genomic Research, announced that he was forming a private company that within three years would unravel the complete genetic code of human life—seven years before the projected finish of the U.S. government’s Human Genome Project. Venter hoped that by decoding the genome ahead of schedule, he would speed up the pace of biomedical research and save the lives of thousands of people. He also hoped to become very famous and very rich. Calling his company Celera (from the Latin for “speed”), he assembled a small group of scientists in an empty building in Rockville, Maryland, and set to work. At the same time, the leaders of the government program, under the direction of Francis Collins, head of the National Human Genome Research Institute at the National Institutes of Health, began to mobilize an unexpectedly unified effort to beat Venter to the prize—knowledge that had the potential to revolutionize medicine and society. The stage was set for one of the most thrilling—and important—dramas in the history of science. The Genome War is the definitive account of that drama—the race for the greatest prize biology has had to offer, told by a writer with exclusive access to Venter’s operation from start to finish. It is also the story of how one man’s ambition created a scientific Camelot where, for a moment, it seemed that the competing interests of pure science and commercial profit might be gloriously reconciled—and the national repercussions that resulted when that dream went awry.
Author: Joram Piatigorsky
Publisher: Harvard University Press
ISBN: 9780674023413
Category : Science
Languages : en
Pages : 434
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Book Description
In Gene Sharing and Evolution Piatigorsky explores the generality and implications of gene sharing throughout evolution and argues that most if not all proteins perform a variety of functions in the same and in different species, and that this is a fundamental necessity for evolution.
Author: Christophe Lambert
Publisher: Academic Press
ISBN: 0128134313
Category : Medical
Languages : en
Pages : 316
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Book Description
Human Genome Informatics: Translating Genes into Health examines the most commonly used electronic tools for translating genomic information into clinically meaningful formats. By analyzing and comparing interpretation methods of whole genome data, the book discusses the possibilities of their application in genomic and translational medicine. Topics such as electronic decision-making tools, translation algorithms, interpretation and translation of whole genome data for rare diseases are thoroughly explored. In addition, discussions of current human genome databases and the possibilities of big data in genomic medicine are presented. With an updated approach on recent techniques and current human genomic databases, the book is a valuable source for students and researchers in genome and medical informatics. It is also ideal for workers in the bioinformatics industry who are interested in recent developments in the field. - Provides an overview of the most commonly used electronic tools to translate genomic information - Brings an update on the existing human genomic databases that directly impact genome interpretation - Summarizes and comparatively analyzes interpretation methods of whole genome data and their application in genomic medicine
Author: Geraldine A. Van der Auwera
Publisher: O'Reilly Media
ISBN: 1491975164
Category : Science
Languages : en
Pages : 496
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Book Description
Data in the genomics field is booming. In just a few years, organizations such as the National Institutes of Health (NIH) will host 50+ petabytesâ??or over 50 million gigabytesâ??of genomic data, and theyâ??re turning to cloud infrastructure to make that data available to the research community. How do you adapt analysis tools and protocols to access and analyze that volume of data in the cloud? With this practical book, researchers will learn how to work with genomics algorithms using open source tools including the Genome Analysis Toolkit (GATK), Docker, WDL, and Terra. Geraldine Van der Auwera, longtime custodian of the GATK user community, and Brian Oâ??Connor of the UC Santa Cruz Genomics Institute, guide you through the process. Youâ??ll learn by working with real data and genomics algorithms from the field. This book covers: Essential genomics and computing technology background Basic cloud computing operations Getting started with GATK, plus three major GATK Best Practices pipelines Automating analysis with scripted workflows using WDL and Cromwell Scaling up workflow execution in the cloud, including parallelization and cost optimization Interactive analysis in the cloud using Jupyter notebooks Secure collaboration and computational reproducibility using Terra
Author: Khaled El Emam
Publisher: "O'Reilly Media, Inc."
ISBN: 1449363032
Category : Computers
Languages : en
Pages : 252
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Book Description
Updated as of August 2014, this practical book will demonstrate proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets. Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others. Understand different methods for working with cross-sectional and longitudinal datasets Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy Use methods to anonymize unstructured free-form text data Minimize the risks inherent in geospatial data, without omitting critical location-based health information Look at ways to anonymize coding information in health data Learn the challenge of anonymously linking related datasets
