Sentence examples for complement experimentation from inspiring English sources

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A biophysically detailed mathematical model of mouse SAN APs will complement experimentation in underpinning the correlation between ion channel function and their genetic bases.

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Accurate modelling complementing experimentation is therefore desirable.

In engineering education, concepts taught through lectures are often complemented by laboratory experimentation.

There are moments when over-saturated drums meet Gregorian chanting and Magnet-style folk oddness (Newspaper Spoons and March of Progress), but the band are at their best when experimentation complements their songwriting rather than defines it.

Hindle (1988, p. X) expressed a conviction that "artifacts, drawings, and photographs provide an entry to the understanding of technology not attainable from the written record alone" Successfully unraveling nineteenth-century patterns required hands-on experimentation complemented by theoretical study.

Unlike many, Pennsylvania Ballet, now under the direction of Roy Kaiser, a former company member, has remained true to its origins as a home for classically trained dancers with individual looks and presences, and for odd choreographic experimentation to complement its Balanchine repertory.

This chapter is written for biologists and biochemists who wish to understand how biophysical modeling can complement a program of biological experimentation.

There are so many contexts in which animals are involved in research and many of the methods held up as alternatives to animal experimentation are really complements, not replacements.

To complement the findings from humans and in vivo experimentation, my laboratory group has investigated the effects of repeated trauma in cultured brain cells using a model of stretch-induced mechanical injury in vitro.

Also, it included results of numerical simulations and experimentation that the participant team had done, complemented with information available in the literature about similar materials or applications.

Of course, causal inference is important in all sectors, but the tech sector — where data abounds and experimentation is feasible — has been a leader in trying to complement intuition with data.

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