Earticle

초록

영어

In recent years, comparative genomic hybridization arrays (aCGH) techniques have been developed rapidly, and aCGH data analysis can identify chromosomal aberrations that are related to the development of many complex diseases. Currently, Chronic Obstructive Pulmonary Disease (COPD) is predicted to become the third most common cause of death and the fifth most common cause of disability in the world by 2020. Unfortunately, So far the studies to COPD have not been well characterized despite the well-documented role that cigarette smoking plays in the genesis of COPD. Therefore, in this study, we used comparative genomic hybridization arrays (aCGH) techniques to detect COPD related susceptibility regions (potential genomic aberrations) which will provide the support for COPD clinical study. Furthermore, the SW-ARRAY algorithm was used to detect the copy number variable (CNV) regions, and these regions were compared between patients with COPD and patients without COPD. Our results can help understand the disease etiology of COPD.

목차

Abstract
 1. Introduction
 2. Materials and Methods
  2.1. Data source
  2.2. aCGH analysis according to probes and samples
  2.3. Detecting CNV regions
 3. Results
  3.1. Common genomic regions in samples with gain and loss
  3.2. Detecting CNV regions according to samples
  3.3. Detecting SNPs
 4. Discussions
 5. Conclusions
 Acknowledgments
 References

키워드

저자

• Lin Hua [ Biomedical Engineering Institute, Capital Medical University ]
• Zheng Yang [ Biomedical Engineering Institute, Capital Medical University ]
• Ping Zhou [ Biomedical Engineering Institute, Capital Medical University ]
• Li An [ Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605