The effect of Fermi-Dirac model in miRNA target prediction.

<p>(A) Overlap of predicted targets from PITA and miRanda using a naïve combination of energy scores. (B) Target overlap between PITA and miRanda using the Fermi-Dirac energy score combination. (C) Receiver-operating Characteristic (ROC) curves of PITA and miRanda predictions with naïve (solid lines) and Fermi-Dirac (broken lines) energy score combination. AUC: area under the curve. Positive and negative sets were derived from the Ago1 IP data (Materials and Methods).</p

Predicting efficiency of Drosophila-trained ComiR on various datasets.

<p>(A) Self-test on the Drosophila Ago1-IP dataset consist of Set I (positive examples) and equal number of negative examples (from Set IV). (B) Performance on an external Drosophila Ago1-IP dataset consisting of Set III (positive examples) and the remaining of Set IV (negative examples). This Drosophila dataset was not used in training ComiR. (C) SN <i>vs.</i> threshold on an external <i>C. elegans</i> AIN-IP dataset (not an ROC curve due to inability to define a negative dataset). (D) Performance on an external human PAR-CLIP dataset. In all cases, TargetScan was used without the evolutionary conservation feature resulting in a binary outcome. For the human dataset the reader can find a continuous TargetScan ROC curve in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002830#pcbi.1002830.s003" target="_blank">Figure S3B</a>, plotted using the <i>context score</i>.</p

<i>Comparison of SVM models for multiple miRNA targets</i>.

<p>Multiple miRNA target scores are combined using the naïve model (red dots) or the ComiR model (FD score or WSUM score). The comparison has been performed on the same datasets as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002830#pcbi-1002830-g003" target="_blank">Figure 3</a> with the exception of the <i>C. elegans</i> dataset, which has no proper ROC curve. Results are arranged by the difference the ComiR combination models offers over the naïve combination model. <i>P</i>: PITA, <i>M</i>: miRanda, <i>T</i>: TargetScan, <i>S</i>: mirSVR. AUC: area under the curve.</p

ComiR schema.

<p>ComiR schema.</p