Streptotrichoseの1例

PDB structures of complexes formed between beta-Catenin and its partners. (PDF 13 kb

visualization2.mp4

the z component of the gradient field in a cross sectio

visualization3.mp4

the relative pressure field with the superposition of the reflected wav

visualization1.mp4

the relative pressure field in a cross sectio

visualization4.mp4

the z component of the gradient field with the superposition of the reflected wav

Additional file 2: Table S2. of Self-regulation of functional pathways by motifs inside the disordered tails of beta-catenin

List of beta-Catenin proteins from eight species. (PDF 8 kb

Additional file 1: of Significant improvement of miRNA target prediction accuracy in large datasets using meta-strategy based on comprehensive voting and artificial neural networks

Table S1. The 1st-step and 2nd-step threshold values for both true and false predictions in eleven DANN modules. Table S2. Sensitivity (Sens), specificity (Spec), and accuracy (Acc) of miRanda, miRDB, PITA, TargetScan, MTR*, and ComiR in the eleven non-redundant datasets under multi-fold cross-validation. Table S3. F1 and Mathews Correlation Coefficient (MCC) of miRanda, miRDB, PITA, TargetScan, MTR*, and ComiR in the eleven non-redundant datasets under multi-fold cross-validation. Table S4. Sensitivity (Sens), specificity (Spec), and accuracy (Acc) of miRanda, miRDB, PITA, TargetScan, MTR*, and ComiR in the eleven independent test datasets. Table S5. F1 and Mathews Correlation Coefficient (MCC) of miRanda, miRDB, PITA, TargetScan, MTR*, and ComiR in the eleven independent test datasets. Figure S1. ROC curves of individual predictors in eleven newly designed datasets that contains duplicate samples. Figure S2. Information gain compared to the distribution of positive and negative samples in four D3 series datasets and six D2 series datasets for (A) miRanda, (B) miRDB, (C) PITA, and (D) TargetScan, when the prediction scores of these predictors are available. (DOCX 642 kb

Comparison between mirMeta and HetroMirPred.

<p>Comparison between mirMeta and HetroMirPred.</p

Performance of meta-predictors using preprocess-I transformation under multi-fold cross validation and in independent dataset.

<p>Performance of meta-predictors using preprocess-I transformation under multi-fold cross validation and in independent dataset.</p

Comparison of true predictions between every two individual predictors for all the 168 negative samples in the D163 dataset.

<p>Comparison of true predictions between every two individual predictors for all the 168 negative samples in the D163 dataset.</p