Sentence examples for prediction benefit from inspiring English sources

Others have found that age is a more important predictor, and comorbidity offers little prediction benefit compared to models using age alone [ 4- 6].

It is also notable that the MGP developed for the FEC/TX treatment arm did not have prediction benefit for patients in the FEC/TX plus trastuzumab treatment arm.

In order to assess how much the PFM prediction benefits from the combination of different sequence derived features through the SVR model, we additionally implemented a nearest neighbor based approach that screens the database of TFs with known PFMs and simply transfers the PFM from the one TF with the most similar binding domain sequence.

Hence, the reliability of disorder prediction benefits from the use of several methods relying on different concepts or different physico-chemical parameters.

The application of the aforementioned approaches for gene function prediction benefits from the use of large data sets where many different experimental treatments or conditions make up the microarray expression dataset (e.g. developmental time points, mutations, specific tissues, environmental conditions, drug treatments, etc).

Additionally, phosphorylation response predictions benefited from more targeted experiments, which looked at 16 phosphoproteins enriched for active signals (Poussin et al., 2014) while GEx data was genome-wide and would only be expected to have a small percentage of genes differentially expressed.

Independent measurement of the levels of both the estrogen receptors, ERα and ERβ, in breast cancer could improve prediction of benefit from endocrine therapies.

Even if this is not the case, our results show that structure prediction may benefit by taking advantage of ideas developed to better understand folding mechanisms.

Whether or not this is the case, our results show that structure prediction may benefit by taking advantage of ideas developed to better understand folding mechanisms.

Several areas of PPIS prediction could benefit from the use of more sophisticated computational learning techniques.

Other aspects of protein structure prediction could benefit from this classification.