Gottlieb et al. developed an efficient computational method PREDICT, to identify drug-disease associations and predict new drug indications.
Carrier females were predicted to be identified by the smaller normal allele bands and full sized mutant product.
The other known Wnt signaling targets are expressed in other cell types or developmental stages, and are not predicted to be identified by our method.
We analyzed predicted DTIs to identify target pairs whose predicted drugs may have synergistic bactericidal effect.
We selected 10% as the cutoff value of predicted probability to identify patients with low survival likelihood and classify patients after prediction.
The molecular electrostatic potential (MEP) was calculated for the predicted models to identify the differences in charge distribution around the active site and its vicinity.
The overlap of pathways was markedly high (70% to 82%) and statistically different, suggesting pathway associations provide a predicted capacity to identify regulatory factors.
InterProScan [ 71] was used on predicted proteins to identify the domain architecture of gene products.
We explored the relationships among VSTs using BLASTclust on predicted proteins to identify putative gene families.
