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. 2014 Apr 14;9(4):e94003. doi: 10.1371/journal.pone.0094003

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© 2014 Henderson, Michailidis

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.

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Upper row: Boxplots showing area under the precision recall curves from 500 Monte Carlo simulations reconstructing the Mouse network. Bottom Row: Boxplots showing area under the ROC curves. Each plot in the row corresponds to a different value of the perturbation parameter (high to low from left to right). Within each plot, boxplots are arranged according to reconstruction method; from left to right these are: additive ODEs (NeRDS), linear ODEs (LM), linear ODEs plus a lasso penalty (Lasso), and Inferelator. For each method a pair of boxplots are presented corresponding to low noise (, left) and moderate noise (, right).

Inline graphic — Upper row: Boxplots showing area under the precision recall curves from 500 Monte Carlo simulations reconstructing the Mouse network. Bottom Row: Boxplots showing area under the ROC curves. Each plot in the row corresponds to a different value of the perturbation parameter (high to low from left to right). Within each plot, boxplots are arranged according to reconstruction method; from left to right these are: additive ODEs (NeRDS), linear ODEs (LM), linear ODEs plus a lasso penalty (Lasso), and Inferelator. For each method a pair of boxplots are presented corresponding to low noise (, left) and moderate noise (, right).