Semi-supervised Multi-View Learning for Gene Network Reconstruction

Semi-supervised Multi-View Learning for Gene Network Reconstruction SynTReN Data: E.coli and Yeast sub-networks, generated expression data and gold standards (Input_Datasets.zip) Interactions predicted by base methods (Base_Method_Predictions.zip) Interactions predicted by our approach - Clustering performed with PCA (Predictions.zip) Interactions predicted by our approach - Clustering performed with K-means (PredictionsK.zip) Dream5 Data: Expression data and gold standards provided by Marbach et al. 2012 [1] (Input_Datasets_D5.zip) Interactions predicted by the considered DREAM5 base methods provided by Marbach et al. 2012 [1] (Base_Method_Predictions_D5.zip) Interactions predicted by our approach - Clustering performed with PCA (Predictions_D5.zip) Interactions predicted by our approach - Clustering performed with K-means (PredictionsK_D5.zip) <em>[1] Marbach, D., Costello, J. C., Kuffner, R., Vega, N. M., Prill, R. J., Camacho, D. M., Allison, K. R., Kellis, M., Collins, J. J., and Stolovitzky, G., Wisdom of crowds for robust gene network inference, Nature Methods, 9, 796-804, 2012.</em>