fulltext.study @t Gmail

A clustering algorithm based on two distance functions for MEC model

Paper ID Volume ID Publish Year Pages File Format Full-Text
15499 1417 2007 3 PDF Available
Title
A clustering algorithm based on two distance functions for MEC model
Abstract

Haplotype reconstruction, based on aligned single nucleotide polymorphism (SNP) fragments, is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. This paper first presents two distance functions, which are used to measure the difference degree and similarity degree between SNP fragments. Based on the two distance functions, a clustering algorithm is proposed in order to solve MEC model. The algorithm involves two sections. One is to determine the initial haplotype pair, the other concerns with inferring true haplotype pair by re-clustering. The comparison results prove that our algorithm utilizing two distance functions is effective and feasible.

Keywords
Haplotype reconstruction; Clustering algorithm; SNP fragment; Distance function; MEC model
First Page Preview
A clustering algorithm based on two distance functions for MEC model
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us
Publisher
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 31, Issue 2, April 2007, Pages 148–150
Authors
, , ,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us