Applied Computational Genomics / Edition 2

Applied Computational Genomics / Edition 2

by Yin Yao
ISBN-10:
981131070X
ISBN-13:
9789811310706
Pub. Date:
09/03/2018
Publisher:
Springer Nature Singapore
ISBN-10:
981131070X
ISBN-13:
9789811310706
Pub. Date:
09/03/2018
Publisher:
Springer Nature Singapore
Applied Computational Genomics / Edition 2

Applied Computational Genomics / Edition 2

by Yin Yao
$109.99
Current price is , Original price is $109.99. You
$109.99 
  • SHIP THIS ITEM
    Qualifies for Free Shipping
  • PICK UP IN STORE

    Your local store may have stock of this item.


Overview

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.

Product Details

ISBN-13: 9789811310706
Publisher: Springer Nature Singapore
Publication date: 09/03/2018
Series: Translational Bioinformatics , #13
Edition description: 2nd ed. 2018
Pages: 150
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

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

Table of Contents

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.

From the B&N Reads Blog

Customer Reviews