02393nam a22003258a 4500001001600000003000700016005001700023006001900040007001500059008004100074020002600115020002900141040002400170050002500194082001800219245018700237264005200424300005900476336002600535337002600561338003600587500007300623520111700696650001301813700004101826700004801867700004601915776003501961856007101996CR9781139226448UkCbUP20180107143411.0m|||||o||d||||||||cr||||||||||||120105s2013||||enk     s     ||1 0|eng|d  a9781139226448 (ebook)  z9781107027527 (hardback)  aUkCbUPcUkCbUPerda00aQH324.2 b.A395 201300a572.8028522300aAdvances in Statistical Bioinformatics :bModels and Integrative Inference for High-Throughput Data / [electronic resource]cEdited by Kim-Anh Do, Zhaohui Steve Qin, Marina Vannucci. 1aCambridge :bCambridge University Press,c2013.  a1 online resource (514 pages) :bdigital, PDF file(s).  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  aTitle from publisher's bibliographic system (viewed on 09 Oct 2015).  aProviding genome-informed personalized treatment is a goal of modern medicine. Identifying new translational targets in nucleic acid characterizations is an important step toward that goal. The information tsunami produced by such genome-scale investigations is stimulating parallel developments in statistical methodology and inference, analytical frameworks, and computational tools. Within the context of genomic medicine and with a strong focus on cancer research, this book describes the integration of high-throughput bioinformatics data from multiple platforms to inform our understanding of the functional consequences of genomic alterations. This includes rigorous and scalable methods for simultaneously handling diverse data types such as gene expression array, miRNA, copy number, methylation, and next-generation sequencing data. This material is written for statisticians who are interested in modeling and analyzing high-throughput data. Chapters by experts in the field offer a thorough introduction to the biological and technical principles behind multiplatform high-throughput experimentation. 0aBiometry1 aDo, Kim-Anh,eeditor of compilation.1 aQin, Zhaohui Steve,eeditor of compilation.1 aVannucci, Marina,eeditor of compilation.08iPrint version: z978110702752740uhttp://dx.doi.org/10.1017/CBO9781139226448zCambridge Books Online