Sentence examples for target likelihood from inspiring English sources

Imposing any cut-off for "target likelihood" is clearly arbitrary but taking, a lower limit of 20 compounds-per-target still covers just over 1000 proteins.

I'm no mathematician, but something loosely based on the following formula might work: proximity of gob to face x velocity/(distance from target + likelihood of somebody's mother having to clean it up).

For a query compound, drugCIPHER-CS will prioritize the proteins in the protein interaction network (i.e. candidate proteins) according to the order of the decreasing drug-target interaction likelihood, and the candidate proteins with high likelihood will be hypothesized as the potential drug-targets [ 16].

Treatment effect on the primary outcome was quantified using relative risk and estimated using targeted maximum likelihood estimation.

The impact of vancomycin/aminoglycosides on kidney function was estimated using targeted maximum likelihood estimation on a risk difference (RD) scale.

To compare the performance of a targeted maximum likelihood estimator (TMLE) and a collaborative TMLE (CTMLE) to other estimators in a drug safety analysis, including a regression-based estimator, propensity score (PS based estimators, and an alternate doubly robust (DR) estimator in a real example and simulations.

As long as the genetic code is available, the letters of code are properly translated, and the therapies accurately targeted, the likelihood of you having a successful treatment in your surgeon's hands increases dramatically.

We used marginal structural models [24] [26] and targeted maximum likelihood estimation [27] to adjust for potential confounders of adherence and viral suppression.

The marginal structural model was fit using a targeted maximum likelihood estimator (TMLE) [27], in order to adjust for the potential confounders listed above.

Because adherence proportion cannot be randomly assigned as an intervention, we relied on a marginal structural model and targeted maximum likelihood estimation of the causal effects of adherence on viral suppression at each time point.

Marginal structural models and targeted maximum likelihood estimation methodologies were used to determine the effect of adherence to antiretroviral therapy on the probability of virologic failure during early and late viral suppression.