Sentence examples for guiding experimentation from inspiring English sources
This framework enables "closing-the-loop" in mammalian cell bioprocess modelling by guiding experimentation through modelling.
The maps are useful for understanding biological systems and for guiding experimentation to achieve optimum artificial contacts.
One simple rule of thumb for guiding experimentation is to start with a large model (larger than seems necessary) to prove that good results are possible.
However, it is offered as non-systematic evidence that GBA has been useful/successful in guiding experimentation.
To understand how useful the model is for guiding experimentation, we also provide the AUC50 the AUC measured up until 50 false positives see(Gribskov and Robinson, 1996).
Many mathematical models have been created in an effort to improve our understanding of biofilters, to guide experimentation, and to improve design of biological treatment systems.
Go-Lab aims to engage students, aged 10 18, in scientific inquiry and facilitate them in acquiring inquiry skills and experience in doing science through guided experimentation.
In line with these recommendations, the Go-Lab project has as its goals encouraging young students to engage in science topics, to acquire scientific inquiry skills, and to experience the culture of doing science under motivating circumstances by undertaking active, guided, experimentation, carried out with more basic and top-level scientific facilities.
In a complex field in which noisy data and expensive experiments constitute the norm, it is crucial to guide experimentation through rational design.
Computational approaches to identify potential host-microbe interaction factors and predict their specific functions can be a valuable way to guide experimentation, and may be the only option for some recalcitrant organisms.
This is an important limitation of the method, but insofar as existing data can be used to guide experimentation, it is still useful as long as one takes into account the authors' caution that "good" algorithmic predictions tend to be generic.
