IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

A Haplotype Analysis System for Genes Discovery of Common Diseases

A Haplotype Analysis System for Genes Discovery of Common Diseases
View Sample PDF
Author(s): Takashi Kido (HuBit Genomix, Inc., Japan)
Copyright: 2009
Pages: 14
Source title: Medical Informatics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Joseph Tan (McMaster University, Canada)
DOI: 10.4018/978-1-60566-050-9.ch161

Purchase

View A Haplotype Analysis System for Genes Discovery of Common Diseases on the publisher's website for pricing and purchasing information.

Abstract

This chapter introduces computational methods for detecting complex disease loci with haplotype analysis. It argues that the haplotype analysis, which plays a major role in the study of population genetics, can be computationally modeled and systematically implemented as a means for detecting causative genes of complex diseases. In this chapter, the author provides a review of issues on haplotype analysis and proposes the analysis system which integrates a comprehensive spectrum of functions on haplotype analysis for supporting disease association studies. The explanation of the system and some real examples of the haplotype analysis will not only provide researchers with better understanding of current theory and practice of genetic association studies, but also present a computational perspective on the gene discovery research for the common diseases.

Related Content

Saloua Mabsor-Zgandaoui, Khawla Rachmoune, Ilham Aftais, Fatima Ezzahra Elamrani, Imade Amradi, Adil El Housseini, Youssef Ait Hamdan, Youness Zgandaoui, Abdelghani Iddar, Mohammed El Mzibri, Adnane Moutaouakkil, Aboubaker El Hessni, Abdelhalim Mesfioui. © 2026. 30 pages.
Yusuf Olatunji Waidi. © 2026. 20 pages.
Ajinkya Nene, Sorour Sadeghzade, Wenjie Yang, Prakash Somani. © 2026. 12 pages.
Seyyed Mohammad Amin Mousavi-Sagharchi, Mahdieh Ranjbar-Jamalabadi, Sama Yavari, Elina Afrazeh, Naresh Poondla, Mohsen Sheykhhasan. © 2026. 32 pages.
Wenqiang Xie, Yuan Su, Ruiqi Zhang, Sijia Li, Jia Ni, Longquan Shao. © 2026. 18 pages.
Zhengao Wang, Huiyu Zhao, Yao Han, Wuyi Zhou, Chengyun Ning. © 2026. 30 pages.
Navya Aggarwal, Shinjini Sen, Tanmay J. Urs, Shreya Gupta, Banashree Bondhopadhyay. © 2026. 36 pages.
Body Bottom