Table 1

Recovery for varying numbers of samples generated from the Mendes networks, which contain an average of ~194 true interactions after self-loops and bidirectional edges are eliminated.
Erdös-Rényi Topology

ARACNE
 Relevance Networks
 DPI Sensitivity
 DPI Precision
 Bayesian Networks
Num samples
 NTP
 NFP
 NTP
 NFP

NTP
 NFP
1000 
 128.00
 1.33
 143.33
 462.67
 99.71%
 96.78%
 50.00
 32.33
750 
 124.33
 2.67
 139.33
 411.00
 99.35%
 96.46%
 45.33
 31.00
500 
 119.00
 1.67
 130.67
 311.33
 99.46%
 96.37%
 41.00
 29.00
250 
 101.00
 4.67
 110.00
 182.33
 97.44%
 95.18%
 24.67
 25.33
125 
 81.00
 4.67
 84.67
 95.00
 95.09%
 96.10%
 5.33
 19.00









Scale-Free Topology

ARACNE
 Relevance Networks
 DPI Sensitivity
 DPI Precision
 Bayesian Networks
Num samples
 NTP
 NFP
 NTP
 NFP

NTP
 NFP
1000 
 97.67
 2.33
 113.33
 234.00
 99.00%
 93.67%
 38.67
 17.00
750 
 90.67
 3.33
 103.00
 200.00
 98.33%
 94.10%
 33.33
 15.33
500 
 80.33
 5.33
 91.67
 154.67
 96.55%
 92.95%
 27.00
 13.33
250 
 63.33
 7.67
 70.00
 80.00
 90.42%
 91.56%
 9.00
 9.67
125 
 46.33
 3.67
 48.00
 49.67
 92.62%
 96.50%
 4.00
 6.00

Recovery for varying numbers of samples generated from the Mendes networks, which contain an average of ~194 true interactions after self-loops and bidirectional edges are eliminated. For all sample sizes ARACNE efficiently eliminates almost all false candidate interactions inferred by RNs, as indicated by the DPI sensitivity (calculated as the percent of false positives eliminated by the DPI), with minimal reduction in true positives, as indicated by the DPI precision (calculated as the percent of false positives removed out of the total number of edges removed by the DPI). Moreover, as the sample size decreases, the number of true connections inferred by ARACNE decays gracefully while the number of false positives remains very low, whereas the performance of Bayesian Networks degrades rapidly for smaller sample sizes as the conditional probability tables become very sparsely populated. Results are calculated using a p-value of 10-4 for ARACNE and Relevance Networks, yielding <0.5 expected false positives for 4,950 potential interactions, and using a Dirichlet prior with equivalent sample size of one for Bayesian Networks [19]. Results are averaged over three network configurations for each topology.

Margolin et al. BMC Bioinformatics 2006 7(Suppl 1):S7   doi:10.1186/1471-2105-7-S1-S7