Predicting <i>Mycobacterium tuberculosis</i> Complex Clades Using Knowledge-Based Bayesian Networks

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="398484.fig.003a" src="https://static.hindawi.com/articles/bmri/volume-2014/398484/figures/398484.fig.003a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>SITVIT-CV</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="398484.fig.003b" src="https://static.hindawi.com/articles/bmri/volume-2014/398484/figures/398484.fig.003b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>CDC-Sublineage</td></tr></table></td></tr></table>

<table>The result of adding rules to different training set sizes for the (a) SITVIT-CV and (b) CDC-Sublineage testbeds.</table>

BioMed Research International

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Figure 3: Predicting <i>Mycobacterium tuberculosis</i> Complex Clades Using Knowledge-Based Bayesian Networks 

BioMed Research International

Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

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