Sentence examples for model we formed from inspiring English sources

Using C3A cells (a hepatocellular carcinoma cell line) as a model, we formed linker-engineered spheroids which grew to a diameter of 250 μm in 7 days, as compared to 16 days using conventional non-adherent culture.

From this model, we formed a pool of candidate models where all covariates and interactions were removed sequentially.

For the implementation of the proposed model, we formed five data sets from these two real data sets (GLS and Septoria), four from the GLS data set and one from the Septoria data set.

To build the initial crystal model, we formed a complete monomer by joining residues 3 182 of our C-terminally truncated monomer to residues 183 243 from our N-terminally truncated monomer.

The combined model we form in this paper illustrates how a quantitative prediction of hazard and survival can be formed that incorporates the predictive capabilities of these three gene expression variables.

Based on these three models, we formed three "scores" for each image, derived by summing the products of the nonzero regression coefficients of the PCs with the corresponding PC values of that image.

Our SAR results, in combination with the HDM2 RING domain receptor recognition model we present, form the basis for the design of drug-like and potent activators of p53 for potential cancer therapy.

Secondly, for more comprehensive evaluation of the effects of potential confounders, we formed models that included the variables in Model 1 together with further adjustments for one of the following covariates: the use of antidepressants (Model 2), the use of NSAIDs (Model 3), and a diagnosis of asthma (Model 4).

First we formed a model that reproduced and combined most cellular, matrix, and physical components that characterize the physiological osteoblastic niche.

In the previous section we formed a model of opsin expression in the guppy cone mosaic that is consistent with the selective pressures of environmental spectra and sexual selection.

We formed statistical models where we controlled for hospital arthroplasty volumes in the analysis of the overall effect of implementation on risk of early revision.