Applied Computational Genomics

The volume provides a 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 field of statistical genomics and will give a detailed introduction to the evolution of the field, as well as critical comments on the advantages and disadvantages of the proposed statistical models. The future directions of translational biology will also be described.

Provides detailed introduction for the evolution of the field Reviews statistical development and application in the area of human genomics Describes the view of future direction towards translational biology ?

Autorentext

Dr. Yin Yao is investigator in the Intramural Research Program at the National Institute of Mental Health, Bethesda, Maryland USA.

Klappentext

The volume provides a 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 field of statistical genomics and will give a detailed introduction to the evolution of the field, as well as critical comments on the advantages and disadvantages of the proposed statistical models. The future directions of translational biology will also be described.

Inhalt

Introduction.- Exploring Polygenic Overlap Between ADHD and OCD.- Concepts of Genetic Epidemiology.- Rare Variants Analysis in Unrelated Individuals.- Whole Genome Association of Treatment Response in OCD.- QTL Mapping of Molecular Traits for Studies of Human Complex Diseases.- From Family Study to Population Study: A History of Genetic Mapping for Nasopharyngeal Carcinoma (NPC).- Test for Nonlinear Dependence of Two Continuous Variables.- Analytical Approaches for Exome Sequence Data.- Machine Learning Approaches: Data Integration for Disease Prediction and Prognosis.- OCD Genomics and Future Looks.