Association Studies OnmtDNA and Parkinson’s Disease Population Discrimination Using the Statistical Classification

ISSN: 2212-392X (Online)
ISSN: 1574-8936 (Print)


Volume 9, 5 Issues, 2014


Download PDF Flyer




Current Bioinformatics

Aims & ScopeAbstracted/Indexed in

Ranking and Category:
  • 20th of 52 in Mathematical & Computational Biology

Submit Abstracts Online Submit Manuscripts Online

Editor-in-Chief:
Alessandro Giuliani
Istituto Superiore di Sanitá (Italian NIH) Environment and Health Dept
Roma
Italy


View Full Editorial Board

Subscribe Purchase Articles Order Reprints

Current: 1.726
5 - Year: 1.577

Association Studies OnmtDNA and Parkinson’s Disease Population Discrimination Using the Statistical Classification

Author(s): Jun Wang, Le Zhang, Quan Zou, Jun Tan, Xiaowei Chen and Yukun Wu

Affiliation: Deptartment of Biostatistics and Computational Biology University of Rochester 601 Elmwood Avenue Box 630, Rochester, New York 14642 USA.

Abstract

Since mitochondrial DNA (mtDNA) follows directly maternal inheritance, the presence of common polymorphisms in mtDNA sequences can classify mtDNAs into haplogroups and sub-haplogroups. Regarding to the rapidly growth of mtDNA sequences, many bioinformatics scientists are dedicated to uncover the association between the common mtDNA polymorphisms and the complex genetic diseases. In this study we analyze the mtDNA sequences from 96 Japanese Parkinson’s disease (PD) patients and 96 Japanese normal persons. A special algorithm based on keyword tree is employed to quickly align the mtDNAs. The mitochondrial single nucleotide polymorphisms (mtSNP) are revealed from the mtDNA alignments by using the genetic characteristic of SNPs and mtDNAs. A statistical significance based locating algorithm is proposed to select the disease associated mtSNPs as the features of classification in disease association research. Sequence transforming probability is introduced in the process of sample classification to discriminate the Parkinson’s disease patients and the common persons. The experimental results indicate that Parkinson’s disease patients can be characterized by unique mtSNPs. Although several mtSNPs are different from previously reported mtSNPs, the algorithm precision of Parkinson’s disease population discrimination reaches 90%.


Purchase Online Rights and Permissions

  
  



Article Details

Volume: 8
First Page: 1
Page Count: 1
DOI: 10.2174/15748936113086660014
Advertisement

Related Journals




Webmaster Contact: urooj@benthamscience.org Copyright © 2014 Bentham Science