沃度保兒謨ニ因セル濕疹

Evaluation of CNA-IC50 correlations by known cancer driver mutations. Distributions of PCCs for cancer cell lines with mutated or wild-type proto-oncogenes or tumor suppressors as depicted in each figure. The rank position of negatively correlated drugs (p < 0.10) is shown. (EPS 975 kb

Schematic view of how to obtain the weighed shared fraction of TFs.

<p>We utilize as prior information that genes which are co-regulated are likely to be effective predictors of each other; the more TFs in common, the more likely to be co-regulated.</p

Spearman rank correlations based on two different inference schemes.

<p>The correlations are based on cross-validations, where the last column stands for an overall calculation based on 24 ranking lists. A minimization of least squares, combined with a penalty term of the form of the elastic net, gives the best performance.</p

Spearman rank correlations for predictions obtained by perfect fits and minimization of L1- and L2-norms.

<p>The correlations are based on cross-validations, where the last column stands for an overall calculation based on 24 ranking lists. The minimization with respect to an L2-norm has the best performance, both for including only expression values and for including both expression values and rates. Following the principle of including as little as possible, we discard the rates.</p

Spearman rank correlations after soft integration of other data sets.

<p>The expression data are obtained from the Rosetta Inpharmatics and ncbi omnibus, and integrated into the inference process by more terms in the objective function. The TF-binding data come from Yeastract and form priors for the penalty term, making it more probable that genes which are co-regulated should act as predictors for each other. Both data sets are only included to the extent the cross-validation procedure allows.</p

Spearman rank correlation for each time point.

<p>The correlations are all with respect to the gold standard. The upper blue curve (stars) is our result; the green curve slightly below (rings) belongs to Ruan <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009134#pone.0009134-Ruan1" target="_blank">[11]</a>, while the lower red curve (plus-signs) is the mean of all other participants. The connecting lines are only guides for the eye. Note how the rankings for some time points obviously are harder to predict than others, and that the results are clearly co-varying.</p

Comparison between Model DvsA and Model AvsT derived from the training set.

<p><b>A</b>) Comparison of the Cov(Tp) of all genes between Model DvsA and Model AvsT; <b>B</b>) Comparison of the Cor(Tp) of all genes between Model DvsA and Model AvsT. D, diluent-challenged CD4⁺ T cells; A, allergen-challenged CD4⁺ T cells; T, allergen-challenged + GC treated CD4⁺ T cells. Cov(Tp), the covariance of the predictive component; Cor(Tp), the correlation of the predictive component.</p

Validation studies of top 547 genes whose expression changed in CD4⁺ T cells from allergic patients after allergen-challenge and were reversed by treatment with glucocorticoids.

<p>The CD4⁺ T cells from allergic patients were obtained from two independent materials and analysed with gene expression microarrays. PCA (<b>A</b> and <b>B</b>) and hierarchical clustering analysis (<b>C</b> and <b>D</b>) of Test1 (<b>A</b> and <b>C</b>) and Test2 (<b>B</b> and <b>D</b>) with the top 547 genes that were changed by allergen challenge and were reversed by GC treatment.</p

PCA modeling of the gene expression microarray data from diluent- (D), allergen- (A) or allergen + GC treated (T) CD4⁺ T cells from patients with seasonal allergic rhinitis in the training set.

<p>PCA modeling of the gene expression microarray data from diluent- (D), allergen- (A) or allergen + GC treated (T) CD4⁺ T cells from patients with seasonal allergic rhinitis in the training set.</p

Pathway analysis of allergen-induced top 547 genes whose expression was reversed by glucocorticoids.

<p>The top 547 genes with a |Cor(Tp)|≥0.5 from the two models were extracted and mapped to Ingenuity pathway analysis. The yellow threshold indicates 95% confidence.</p