Generation and Analysis of Large-Scale Data-Driven <i>Mycobacterium tuberculosis</i> Functional Networks for Drug Target Identification

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="801478.fig.006a" src="https://static.hindawi.com/articles/abi/volume-2011/801478/figures/801478.fig.006a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b>Variations in the closeness measure</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="801478.fig.006b" src="https://static.hindawi.com/articles/abi/volume-2011/801478/figures/801478.fig.006b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Variations in the confidence metric</td></tr></table></td></tr></table>

<table>Assessing the variations in closeness and confidence centrality measures in terms of protein category.</table>

Advances in Bioinformatics

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Figure 6

Figure 6: Generation and Analysis of Large-Scale Data-Driven <i>Mycobacterium tuberculosis</i> Functional Networks for Drug Target Identification 

Advances in Bioinformatics

Generation and Analysis of Large-Scale Data-Driven Mycobacterium tuberculosis Functional Networks for Drug Target Identification

Figure 6