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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.

Molecular medicine is an applied science focused on human genes/transcripts, proteins, metabolites, and metabolic networks that describes molecular and cellular processes of health and disease onset and progression. Molecular medicine-based integrative identification and characterization of biomarker targets and their clinical translations is essential to explain/decipher the mechanism(s) underlying physiological pathways and pathological conditions, and acquire cell-targeted early interventional and therapeutic strategies in the context of precision medicine and public health. Principally, Molecular Medicine provides an overview of the latest headlines/developments of systems and molecular medicine, highlighting the emerging high-throughput technologies, promising potential applications, and progress in biomedical research and development strategies.

Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed. Examples of applications in real environmental, clinical and food analysis cases help readers disseminate these approaches. Chapters of note include an Introduction to Data Analysis Relevance in the Omics Era, Omics Experimental Design and Data Acquisition, Microarrays Data, Analysis of High-Throughput RNA Sequencing Data, Analysis of High-Throughput DNA Bisulfite Sequencing Data, Data Quality Assessment in Untargeted LC-MS Metabolomic, Data Normalization and Scaling, Metabolomics Data Preprocessing, and more. Presents the best reference book for omics data analysis Provides a review of the latest trends in transcriptomics and metabolomics data analysis tools Includes examples of applications in research fields, such as environmental, biomedical and food analysis

Due to population aging, calcific aortic valve disease (CAVD) has become the most common heart valve disease in Western countries. No therapies exist to slow this disease progression, and surgical valve replacement is the only effective treatment. Calcific Aortic Valve Disease covers the contemporary understanding of basic valve biology and the mechanisms of CAVD, provides novel insights into the genetics, proteomics, and metabolomics of CAVD, depicts new strategies in heart valve tissue engineering and regenerative medicine, and explores current treatment approaches. As we are on the verge of understanding the mechanisms of CAVD, we hope that this book will enable readers to comprehend our current knowledge and focus on the possibility of preventing disease progression in the future.

This book provides a comprehensive guide to scientists, engineers, and students that employ metabolomics in their work, with an emphasis on the understanding and interpretation of the data. Chapters guide readers through common tools for data processing, using database resources, major techniques in data analysis, and integration with other data types and specific scientific domains. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, practical guidance of methods and techniques, useful web supplements, and connect the steps from experimental metabolomics to scientific discoveries. Authoritative and cutting-edge, Computational Methods and Data Analysis for Metabolomics to ensure successful results in the further study of this vital field.