Big Data in Omics and Imaging - Association Analysis

Zusatztext "This is a fantastic book intensively focusing on the mathematical underpinnings of modern genome-wide association studies (GWAS). It serves well for senior graduate students in applied mathematics! computer science! and statistics who are interested in building a solid mathematical understanding of GWAS. Backgrounds of advanced mathematics and genetics are expected. It can also be used as a handbook for professionals to quickly check mathematical contexts of GWAS approaches and tools. This book is especially helpful for the latest generation of statistical geneticists who are pursuing academic career paths."~Journal of the American Statistical Association! Jing Su (Wake Forest School of Medicine) Informationen zum Autor Momiao Xiong , is a professor in the Department of Biostatistics, University of Texas School of Public Health, and a regular member in the Genetics & Epigenetics (G&E) Graduate Program at The University of Texas MD Anderson Cancer Center, UTHealth Graduate School of Biomedical Science. Zusammenfassung The text provides unified frameworks, basic knowledge and efficient computational tools for analyzing growing large, complex and diverse genomic, epigenomic, physiological and image data. It introduces currently developed statistical methods and software for big genomic and epigenomic data analysis with real-world examples and case studies. Inhaltsverzeichnis Mathematical Foundation. Linkage Disequilibrium. Association Studies for Qualitative Traits. Association Studies for Quantitative Traits. Multiple Phenotype Association Studies.

Détails du produit

• Auteurs: Joshua Akey, Joshua (University of Washington Akey, Momiao Xiong, Momiao (University of Texas School of Publi Xiong, Momiao (University of Texas School of Public Health Xiong, Momiao Akey Xiong, Xiong Momiao
• Edition: Taylor & Francis Ltd.
• Langues: Anglais
• Format d'édition: Livre Relié
• Sortie: 13.12.2017
• EAN: 9781498725781
• ISBN: 978-1-4987-2578-1
• Pages: 668
• Thèmes: Chapman & Hall/CRC Mathematical and Computational Biology; Chapman & Hall/CRC Mathematical and Computational Biology; Chapman & Hall/CRC Computational Biology Series
• Catégories: Sciences naturelles, médecine, informatique, technique > Biologie; MATHEMATICS / Probability & Statistics / General, SCIENCE / Life Sciences / Biology, SCIENCE / Biotechnology, Biology, life sciences, Databases, Databases / Data management