Sentence examples for biological data to design from inspiring English sources

It is hoped that this review paper will provide logical ways of efficiently utilizing 'big' biological data to design and develop novel metabolic pathways for the production of various bulk chemicals that are currently produced from fossil resources.

Finally, it is known that the climbing ability and physical characteristics are necessary data to design a diversified biological environment for various species of frogs.

These considerations suggest that, in applying biological data to robotic design, proper 'size' should be maintained across all levels (i.e., if small-animal neural mechanisms are used, so should small-animal muscle and biomechanical properties).

Furthermore, we show that designing ground-truth samples on the basis of the acoustic diversity data allows the biological data to "speak" for itself.

Experiments on both simulated and biological data are designed to investigate the properties of the proposed method and existing methods.

Synthetic biology is an emerging market that uses biological engineering to design living organisms to make products, such as flavors, fragrances and probiotics.

The explosive growth in the amount of public domain-available chemical and biological data has generated huge effort to design, analyze, and apply novel learning methodologies.

For whole effluent assessment, biomarker data can be used to design cost-effective biological and chemical monitoring programs to reduce ecological impacts in receiving waters.

In order to facilitate truly exploratory biological data mining we have designed and implemented a system where footprints over genomic features ranging in the order of hundreds of thousands can be rapidly constructed once the binary representation of the signals has been built.

These analyses are used to establish the statistical nature and probe the biological relevance of the data being generated, and also to design and analyze experiments accordingly.

This work demonstrates the use of statistical methods to design biological decontamination experiments at the limits of decontamination technology and to analyze the resultant data.