Sentence examples for integrate such information from inspiring English sources

A fundamental challenge when learning new information is determining how to integrate such information into our pre-existing body of knowledge.

With this goal in mind, the workability of a given strategy largely depends on how we deal with diverse germplasm and how we reliably phenotype materials and identify useful genes with minor effects, to integrate such information into our research flow.

Nevertheless, as long as the quantitative experimental data are available that captures such differences, we can further adjust the model to integrate such information, by increasing the discrete levels and applying more subtle rules.

The challenge now is to find ways to integrate such information in order to facilitate the discovery of disease-specific knowledge and targets, as well as their reproducibility using different data sources.

How to integrate such information into the pan-caner stratifications is of great interest and worth exploring in further study.

The critical challenge facing cancer genomics today is to analyze and integrate such information in the most efficient and meaningful way to advance cancer biology, and then to translate that knowledge to clinic [ 1, 2].

We detail how each agent computes the Agent Satisfaction by acquiring sensor perceptions through an omnidirectional vision system, extracting aggregated information from the acquired perception, and integrating such information with that communicated by the teammates.

Rather than treat each user and patient equally, we believe that detection sensitivity could be improved by integrating such information into the network modeling process.

Integrating such information can provide a much fuller inventory of the ecosystem to which the target species belongs than is now possible.

The proposed method is an example of integrating such information to increase the power and specificity in peak detection.

For example, DNase I hypersensitivity and certain histone marks together could identify regulatory regions active in particular cell types that are far away from their target genes [ 9], while integrating such information with sequence motifs could further predict the transcription factors involved in the gene regulation.