Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data. It is an excellent resource for students and professionals involved with gene or protein expression data in a variety of settings.

The patenting and licensing of human genetic material and proteins represents an extension of intellectual property (IP) rights to naturally occurring biological material and scientific information, much of it well upstream of drugs and other disease therapies. This report concludes that IP restrictions rarely impose significant burdens on biomedical research, but there are reasons to be apprehensive about their future impact on scientific advances in this area. The report recommends 13 actions that policy-makers, courts, universities, and health and patent officials should take to prevent the increasingly complex web of IP protections from getting in the way of potential breakthroughs in genomic and proteomic research. It endorses the National Institutes of Health guidelines for technology licensing, data sharing, and research material exchanges and says that oversight of compliance should be strengthened. It recommends enactment of a statutory exception from infringement liability for research on a patented invention and raising the bar somewhat to qualify for a patent on upstream research discoveries in biotechnology. With respect to genetic diagnostic tests to detect patient mutations associated with certain diseases, the report urges patent holders to allow others to perform the tests for purposes of verifying the results.

In the last decade DNA sequencing costs have decreased over a magnitude, largely because of increasing throughput by incremental advances in tools, technologies and process improvements. Further cost reductions in this and in related proteomics technologies are expected as a result of the development of new high-throughput techniques and the computational machinery needed to analyze data generated. Automation in Proteomics & Genomics: An Engineering Case-Based Approach describes the automation technology currently in the areas of analysis, design, and integration, as well as providing basic biology concepts behind proteomics and genomics. The book also discusses the current technological limitations that can be viewed as an emerging market rather than a research bottleneck. Topics covered include: molecular biology fundamentals: from ‘blueprint’ (DNA) to ‘task list’ (RNA) to ‘molecular machine’ (protein); proteomics methods and technologies; modelling protein networks and interactions analysis via automation: DNA sequencing; microarrays and other parallelization technologies; protein characterization and identification; protein interaction and gene regulatory networks design via automation: DNA synthesis; RNA by design; building protein libraries; synthetic networks integration: multiple modalities; computational and experimental methods; trends in automation for genomics and proteomics new enabling technologies and future applications Automation in Proteomics & Genomics: An Engineering Case-Based Approach is an essential guide to the current capabilities and challenges of high-throughput analysis of genes and proteins for bioinformaticians, engineers, chemists, and biologists interested in developing a cross-discipline problem-solving based approach to systems biology.

Introduction to the proteome (K. L. Williams, D. F. Hochstrasser). Two-dimensional electrophoresis: the state of the art and future directions (B. R. Herbert, J.-C. Sanchez, L. Bini). large-scale comparative protein modeling ( M. C. Peitsch, N. Guex); Clinical and biomedical applications of proteomics (D. F. Hochstrasser). Biological applications of proteomics (K. L. Williams, V. Pallini). Conclusions (D. F. Hochstrasser, L. Williams). Index.

The new field of toxicogenomics presents a potentially powerful set of tools to better understand the health effects of exposures to toxicants in the environment. At the request of the National Institute of Environmental Health Sciences, the National Research Council assembled a committee to identify the benefits of toxicogenomics, the challenges to achieving them, and potential approaches to overcoming such challenges. The report concludes that realizing the potential of toxicogenomics to improve public health decisions will require a concerted effort to generate data, make use of existing data, and study data in new waysâ€"an effort requiring funding, interagency coordination, and data management strategies.

Current applications and recent advances in genomics and proteomics Genomics and Proteomics Engineering in Medicine and Biology presents a well-rounded, interdisciplinary discussion of a topic that is at the cutting edge of both molecular biology and bioengineering. Compiling contributions by established experts, this book highlights up-to-date applications of biomedical informatics, as well as advancements in genomics-proteomics areas. Structures and algorithms are used to analyze genomic data and develop computational solutions for pathological understanding. Topics discussed include: Qualitative knowledge models Interpreting micro-array data Gene regulation bioinformatics Methods to analyze micro-array Cancer behavior and radiation therapy Error-control codes and the genome Complex life science multi-database queries Computational protein analysis Tumor and tumor suppressor proteins interactions