Sentence examples for use of multiple experimental from inspiring English sources
Our results indicate that the use of multiple experimental models in therapeutic studies is crucial.
One reason for the current lack of clarity likely stems from the use of multiple experimental systems, each optimized to analyse specific steps in the mRNA translation/turnover pathway.
The unifying concept behind our experimental strategy is the use of multiple experimental paradigms for the prospective analysis of clinically relevant samples obtained from the same patient, along with the systematic integration of the biological and clinical data.
Further development of theoretical and systems biology together with the use of multiple experimental methods for biological experiments could also be helpful in the context of years and decades.
It is unlikely that any single available technology will capture all genome structural variations and the use of multiple experimental methods (sequence assembly comparisons, paired-end sequencing, sequencing analysis and high-resolution tiling arrays) will be needed to unravel the complexity of genome variations.
Finally, the reliability of using a universal RNA reference for two-channel microarrays was tested and the results suggest that comparisons of multiple experimental conditions using the same control can be accurate.
The MDV software could be particularly helpful to other biofilm-related fields using whole-genome profiling for comparison of multiple experimental conditions, such as comparative-transcriptome of distinct strains or in response to therapeutic agents.
An absolute value describing N peptide-HSP72 interaction is thus best represented by combining results of multiple experimental trials using freshly prepared sensor surfaces.
These codon-optimized versions of mTFP1 and mCherry have promising potential for use in multiple experimental applications.
Analysis data on the other hand is very complex to describe because of its direct relation to the raw data it derives from (e.g. use of multiple input files representing experimental and computed data) and the existence of numerous analysis methods that can be problem-specific (e.g. Protein vs. RNA, QM vs. MD).
The use of multiple ontologies to annotate experimental data brings with it a considerable overhead.
