Applied Computational Genomics [electronic resource] /
Shugart, Yin Yao.editor.
"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland, USA.
Description based upon print version of record.
Includes bibliographical references and index.
Introduction -- Concepts of Genetic Epidemiology -- Integration of Linkage Analysis and Next Generation Sequencing Data -- From Family Study to Population Study: A history of Genetic Mapping for Nasopharyngeal Carcinoma (NPC) -- QTL Mapping of Molecular Traits for Studies of Human Complex Diseases -- Renewed Interest in Haplotype: from Genetic Marker to Gene Prediction -- Analytical Approaches for Exome Sequence Data -- Rare Variants Analysis in Unrelated Individuals -- Gene Duplication and Functional Consequences -- From GWAS to Next-Generation Sequencing on Human Complex Diseases: the Implications for Translational Medicine and Therapeutics.
"Applied Computational Genomics" focuses on an in-depth review of statistical development and application in the area of human genomics including candidate gene mapping, linkage analysis, population-based, genome-wide association, exon sequencing and whole genome sequencing analysis. The authors are extremely experienced in the area of statistical genomics and will give a detailed introduction of the evolution in the field and critical evaluations of the advantages and disadvantages of the statistical models proposed. They will also share their views on a future shift toward translational biology. The book will be of value to human geneticists, medical doctors, health educators, policy makers, and graduate students majoring in biology, biostatistics, and bioinformatics. Dr. Yin Yao Shugart is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland, USA.
Human genetics.
Bioinformatics.
Biotechnology.
Human Genetics.
Bioinformatics.
Biotechnology.