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OverviewIn most modern biomedical research projects, application of high-throughput genomic, proteomic, and transcriptomic experiments has gradually become an inevitable component. Popular technologies include microarray, next generation sequencing, mass spectrometry and proteomics assays. As the technologies have become mature and the price affordable, omics data are rapidly generated, and the problem of information integration and modeling of multi-lab and/or multi-omics data is becoming a growing one in the bioinformatics field. This book provides comprehensive coverage of these topics and will have a long-lasting impact on this evolving subject. Each chapter, written by a leader in the field, introduces state-of-the-art methods to handle information integration, experimental data, and database problems of omics data. Full Product DetailsAuthor: George Tseng (University of Pittsburgh) , Debashis Ghosh (Pennsylvania State University) , Xianghong Jasmine Zhou (University of Southern California)Publisher: Cambridge University Press Imprint: Cambridge University Press Dimensions: Width: 15.60cm , Height: 3.00cm , Length: 23.50cm Weight: 0.820kg ISBN: 9781107069114ISBN 10: 1107069114 Pages: 476 Publication Date: 23 September 2015 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In stock We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationGeorge Tseng completed his Sc.D. in biostatistics with a concentration in genomics from the Harvard School of Public Health. He is currently a Professor of Biostatistics, Human Genetics, and Computational and Systems Biology at the University of Pittsburgh. His research interests focus on statistical and computational method development for analyzing high-throughput omics data. Debashis Ghosh completed his Ph.D. in biostatistics from the University of Washington. After serving on the faculty in the Department of Biostatistics at the University of Michigan and in the Department of Statistics at Pennsylvania State University, he is currently Chair and Professor in the Department of Biostatistics and Informatics at the Colorado School of Public Health. His interests in statistical genomics have primarily focused on the development of novel methods for integration of high-throughput data from different platforms. These motivating problems have also led to lines of methodologic research in the areas of multiple comparisons procedures, machine learning techniques and Empirical Bayes procedures. Ghosh is a recipient of several awards including Fellow of the American Statistical Association and the 2013 recipient of the Mortimer Spiegelman Award, for early career contributions of statistics in applied public health problems. Jasmine Zhou completed her Ph.D. at the Swiss Federal Institute of Technology (ETH Zurich), and conducted her post-doc training at Harvard University. She is currently a professor of biological sciences and computer science at the University of Southern California. Dr Zhou is the PI of the NIH center for knowledge base on disease connections within the MAPGen consortium. Dr Zhou heads the laboratory of computational integrative genomics at the University of Southern California, addressing the 'Big Data' challenges brought by the enormous amount of extremely diverse genomic data in public repositories. She was a recipient of several awards including an Alfred Sloan fellowship and a NSF Career award. Tab Content 6Author Website:Countries AvailableAll regions |