DocumentCode :
2190854
Title :
Isolating - a new resampling method for gene order data
Author :
Shi, Jian ; Arndt, William ; Hu, Fei ; Tang, Jijun
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Carolina, Columbia, SC, USA
fYear :
2011
fDate :
11-15 April 2011
Firstpage :
1
Lastpage :
6
Abstract :
The purpose of using resampling methods on phylogenetic data is to estimate the confidence value of branches. In recent years, bootstrapping and jackknifing are the two most popular resampling schemes which are widely used in biological research. However, for gene order data, traditional bootstrap procedures can not be applied because gene order data is viewed as one character with various states. Experience in the biological community has shown that jackknifing is a useful means of determining the confidence value of a gene order phylogeny. When genomes are distant, however, applying jackknifing tends to give low confidence values to many valid branches, causing them to be mistakenly removed. In this paper, we propose a new method that overcomes this disadvantage of jackknifing and achieves better accuracy and confidence values for gene order data. Compared to jackknifing, our experimental results show that the proposed method can produce phylogenies with lower error rates and much stronger support for good branches. We also establish a theoretic lower bound regarding how many genes should be isolated, which is confirmed empirically.
Keywords :
evolution (biological); genetics; genomics; sampling methods; biological reserach; bootstrapping; gene order data resampling method; gene order phylogeny; genomes; isolating method; jackknifing; Accuracy; Biological cells; Genomics; History; Phylogeny; Radio frequency;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2011 IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9896-3
Type :
conf
DOI :
10.1109/CIBCB.2011.5948464
Filename :
5948464
Link To Document :
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