Sentence examples for streamlined validation from inspiring English sources

I outline four reasons why bioinformaticians are newly enabled to drive the questions in primary medical discovery: public availability of data, intersection of data across experiments, commoditization of methods, and streamlined validation.

Our resource and methods are ideal for streamlined validation of fusions newly identified by next-generation sequencing, and they pave the way to studying the impact of fusion expression variability on clinical outcome.

The distribution derived in this study can be used as a bench mark against which to evaluate LOD50 data generated in future studies of detection methods for Salmonella in foods and potentially offers a possible way to streamline method validation study experimental design.

Besides maintaining the key benefits of culture tests, the rapid method presented here should streamline regulatory validation since it is based on the same underlying principles and procedures as the regulatory gold standard.

Those who apply their research to publicly available data, commoditized tools, and streamlined paths through validation will be able to create novel diagnostics and discover fundamental causes of disease as targets for therapies.

We developed a streamlined and easy-to-follow approach to the design, validation and annotation of species-specific array probes.

To achieve this goal, we developed a streamlined and easy-to-follow approach to the design, validation and annotation of species-specific array probes, particularly for organisms whose genomes have yet to be fully sequenced and annotated.

Compared to rapid methods that differ greatly from the traditional method, regulatory validation for the new method should be substantially streamlined.

Accordingly, this tool has the potential to significantly streamline the verification and validation (V and V) processes in NRS code development environments which are characterized by rapidly evolving software, many contributing developers and a large and growing body of validation data.

Close collaboration between pharmaceutical companies, biotechnology companies and academic institutions during the many intricate phases of drug discovery is necessary to address the need to co-ordinate and streamline target discovery and validation activities, which typically take much longer than anticipated.

tDAR is able to operate at scale by performing only technical validation and streamlining data deposition with a minimum of mandatory description.