Genomic and Personalized Medicine
Author | : Geoffrey S. Ginsburg |
Publisher | : Academic Press |
Total Pages | : 1343 |
Release | : 2012-11-29 |
ISBN-10 | : 9780123822277 |
ISBN-13 | : 0123822270 |
Rating | : 4/5 (77 Downloads) |
Book excerpt: Genomic and Personalized Medicine, Second Edition - winner of a 2013 Highly Commended BMA Medical Book Award for Medicine - is a major discussion of the structure, history, and applications of the field, as it emerges from the campus and lab into clinical action. As with the first edition, leading experts review the development of the new science, the current opportunities for genome-based analysis in healthcare, and the potential of genomic medicine in future healthcare. The inclusion of the latest information on diagnostic testing, population screening, disease susceptability, and pharmacogenomics makes this work an ideal companion for the many stakeholders of genomic and personalized medicine. With advancing knowledge of the genome across and outside protein-coding regions of DNA, new comprehension of genomic variation and frequencies across populations, the elucidation of advanced strategic approaches to genomic study, and above all in the elaboration of next-generation sequencing, genomic medicine has begun to achieve the much-vaunted transformative health outcomes of the Human Genome Project, almost a decade after its official completion in April 2003. Highly Commended 2013 BMA Medical Book Award for Medicine More than 100 chapters, from leading researchers, review the many impacts of genomic discoveries in clinical action, including 63 chapters new to this edition Discusses state-of-the-art genome technologies, including population screening, novel diagnostics, and gene-based therapeutics Wide and inclusive discussion encompasses the formidable ethical, legal, regulatory and social challenges related to the evolving practice of genomic medicine Clearly and beautifully illustrated with 280 color figures, and many thousands of references for further reading and deeper analysis