Sentence examples for genomics science from inspiring English sources

Genomics science facilitates characterization of entire eukaryote genomes at the DNA sequence level, but for crop plants with complex genomes such as sugarcane, gene characterization is currently best achieved via expressed sequence tag (EST) analysis where sequence information is restricted to genes that are actually functioning in a particular tissue or situation.

The agricultural research paradigm then broke down once more, with the development of genomics science and our understanding of life at a deeper level, that of the gene (Buttel et al.[1985]).[1985]

The two revolutions witnessed in relation to plant improvement, pertaining first to our understanding of genetics and rules of heredity, and second to the development of molecular biology and genomics science, have considerably altered the agricultural research paradigm and industry structure (Barton [2003]).

With the introduction of genomics science and technology over the past two decades, it has evolved from the predecessor field of pharmacogenetics that has mid-20th century origins in early studies of monogenic variations in drug metabolism.

In the last decade, several data preservation, management, sharing policies, and plans have emerged in response to increased funding for high-throughput approaches in genomics and functional genomics science [ 1].

Although the translation of this knowledge to the clinical practice is still minimal, the genomics sciences are inexorably changing our understanding of the biology of a myriad of medical conditions.

To test whether the resulting distributions of parameter values were enriched in the sets of kinetic solutions among those 10 (NFBLB) parameter sets sampled, we adopted an enrichment test that has found many uses in genomics sciences [ 43, 44].

As in the enrichment test employed in genomics sciences [ 43, 44], we can then compute the p-value to measure the statistical significance of the likelihood for observing x i when the null distribution (equation (10)) is assumed to be the true count distribution.

We provide examples of Mode 2 knowledge in pharmacogenomics, such as citizen science, and discuss the implications for post-genomics science.

Our working premise is that to truly enable a robust public health pharmacogenomics R&D landscape, post-genomics science warrants a 'third pillar' whereby the political determinants of health are recognized and taken seriously, as much as the social and biological determinants of health [ 19- 23].

and successfully defended a research thesis grounded in extensive training in biochemistry, genomics, computer science, or another area of science.