Sentence examples for research using models from inspiring English sources

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Additional research using models from the Hazardous Air Pollutants program found associations between autism and air toxics at the birth residence of children from North Carolina and West Virginia (Kalkbrenner et al. 2010).

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Over the next 7 years, Cairns fostered basic biological research using model organisms such as bacteria, flies, slime molds, amphibians and mice to understand fundamental biological pathways that were likely to be relevant to the transformation of normal cells into cancer cells.

Mendel's basic laws of genetics were expanded upon in the early 20th century when molecular geneticists began conducting research using model organisms such as Drosophila melanogaster (also called the vinegar fly or fruit fly) that provided a more comprehensive view of the complexities of genetic transmission.

More commonly, research using model species is usually used in comparisons within phylogenetic boundaries, i.e. plant, animal or fungi.

A major difference to previous pharmacological research using modeling and simulation is the implementation of the proper target engagement by the drugs in the clinical situation.

In some cases, research using model organisms has distinct advantages compared with human cell culture systems or other human population-based approaches.

Based on research using model organisms, studies that have extended the scope of our understanding of human aging were also presented at the meeting.

An additional benefit from the identification of variables robustly associated with long-term human survival is the potential that, by "reverse translation", such variables will suggest new endpoints for evaluation in basic aging research using model organisms [ 111, 112].

Translating folding/unfolding principles from nature, candidate geometries were developed and researched using models, drawings and visualisations.

This quantitative research uses modeling and simulation, high-performance computing, and large-scale data analysis to create testable hypotheses about mechanisms driving complex biological function.

Some researches using model predictive control (MPC) based on simulations may result in error due to uncertain data input.

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