Sentence examples for using traditional experimental methods from inspiring English sources

Single perturbations of a system (e.g. inhibiting an enzyme) are commonly studied using traditional experimental methods, but combinations of perturbations, too numerous to study experimentally, can be examined using computational tools (Koch et al., 2009), based on existing models that describe the effects of single drugs.

Using traditional experimental methods for this purpose can be very costly and time-consuming, and also uncertain since animal models are not always good predictors for pathogenicity in humans.

Numerous studies of gene methylation have used traditional experimental methods to generate large amounts of methylation data; more recently, a large number of genome-wide DNA methylomes have been generated through the traditional methods being combined with the high throughput technologies.

If it is uncertain whether regulators will accept a QSAR prediction, then industry will prefer to use a traditional experimental method in order to avoid uncertainty and delay in regulatory approval.

SGD and BIOGRID collect and organize biological information on proteins and their interactions of the budding yeast S. cerevisiae, but we also used published data [ 4] from traditional experimental methods and also from computational predictions, as these can give additional valuable information.

The approach can be used to identify numerous drug targets more cheaply and easily than traditional experimental methods, the researchers report this week in PLoS Computational Biology.

Limits of traditional experimental methods include the costs and time they need, ethical concern about use of animals, and the relatively small number of laboratories that can do the experiments.

However, traditional experimental methods are not always practical or possible.

However, these traditional experimental methods are time-consuming and expensive, especially for genome-wide scale.

Traditional experimental methods for function characterization cannot cope with the rate at which genomics efforts are generating data.

Traditional experimental methods required an investment of labour and resources that was roughly linear in the number of proteins studied.