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Bioinformatics 2007 23(8):1046-1047; doi:10.1093/bioinformatics/btm075
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© The Author 2007. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Maximum likelihood of phylogenetic networks

Guohua Jin , Luay Nakhleh , Sagi Snir and Tamir Tuller

Bioinformatics (2006) 22(21), 2604–2611

The authors would like to apologize for errors of graph misplacement in Figures 4–6GoGo, and an error in the caption of Figure 6. The correct figures and their captions are shown below.


Figure 1
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Fig. 4. The species tree of the 14 organisms, as reported by Tailliez et al. (2002), and the four HGT edges inferred by our heuristic for the big ML problem. Likelihood criterion = ancestral, and tree criterion = all.

 

Figure 2
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Fig. 5. The improvement in the likelihood score as a function of the number of HGT edges added to the species tree (shown in Fig. 4). The improvement achieved by adding the fourth HGT edge is smaller compared to that achieved by adding the first three events, which indicates that three HGT events suffice to model the evolution of the ribosomal protein rpl12e gene for these 14 archaea. Likelihood criterion = ancestral, and tree criterion = all.

 

Figure 3
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Fig. 6. The improvement in the likelihood score as a function of the number of HGT edges added to the species tree (shown in Fig. 3). The improvement achieved by adding the sixth HGT edge is smaller compared to that achieved by adding the first five events, which indicates that five HGT events suffice to model the evolution of the rbcL gene for these 15 organisms. Likelihood criterion = ancestral, and tree criterion = all.

 

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Related articles in Bioinformatics:

Maximum likelihood of phylogenetic networks
Guohua Jin, Luay Nakhleh, Sagi Snir, and Tamir Tuller
Bioinformatics 2006 22: 2604-2611. [Abstract] [FREE Full Text]  




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