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. 2013 Jul 6;7:57. doi: 10.1186/1752-0509-7-57

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Copyright © 2013 Santra et al.; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Network reconstruction from incomplete perturbation data.X-axis represents the number of perturbations and Y-axis represents AUROC in panel (a) and AUPR in panel(b). The error-bars indicate the standard deviations of the corresponding AUROCs in panel (a) and AUPRs in panel (b). The results suggest that the networks reconstructed by BVSA is significantly more accurate than both LMML and random guesses even when only half of the MAPK modules were perturbed and no repetitions of the experiments were available.