A reliable and fast method that would test VLS predictions and identify hits could help accelerate the drug-discovery process.
Above and beyond summarizing research findings, we discuss how taxes are commonly implemented in agency models, derive empirical predictions, and identify research gaps for future tax research.
Beyond summarizing the research findings by tax types (corporate income, wage, bonus, and shareholder taxes) and research area (compensation, investments, tax avoidance, and transfer pricing), we also discuss how taxes are commonly implemented into agency models, derive empirical predictions, and identify research gaps for future tax research.
We used the 438 promoters and 464 enhancers that Won et al. reported in ENCODE region as additional filters to remove false positives of cis-module predictions and identify functional sites in the HeLa cell.
The results support the IMB model's predictions and identify modifiable and intervenable determinants of diabetes medication adherence.
They modeled per-flow throughput prediction and identified dominant and starving flows in the network.
We compared the gene models generated by EVM with the updated grape gene prediction and identified a set of 6,381 new potential genes.
They used the network strategy in cancer-associated gene prediction and identified one gene that encodes hyaluronan-mediated motility receptor (HMMR) and directly interacts with the well-known breast cancer-associated gene breast cancer 1, early onset (BRCA1).
Therefore, we performed in silico target prediction and identified an additional three, nine and 24 MYB genes for miR159, miR828 and miR858, respectively, with an align score of less than 5. Thus, a total of 49 MYB target genes were found, four for miR159, 12 for miR828 and 40 for miR858.
In our approach, the use of computational chemoinformatics enabled the generation of hit compound network similarity graphs that grouped compounds based on chemotypes, facilitated compound target and off-target prediction, and identified analogs of validated inhibitors with the potential to be more potent, more specific, or less toxic.
