Sentence examples for with strong preference from inspiring English sources

Exact(10)

Our in vitro activity assays showed that AAE15 is an AAS with strong preference for C10, C12, and C14 substrates, but can also activate other fatty acids with greatly reduced efficiency.

Here we investigated the targeting of cuts early in DNA fragmentation by apoptosis of chicken liver cells and discovered that a small number of specific open chromatin regions were attacked with strong preference.

This commitment became especially apparent during discussions of case scenarios describing patients with mild symptoms but with strong preference for referral or patients with severe symptoms with strong preference against referral.

The data also reveal spacer sequence dependent variation in activity with strong preference at a single position (for G at position 1) and weaker preference at another position.

In particular we have studied the operon organisation of the relevant genomes, trying to elucidate important characteristics of genes with strong preference for operon organisation compared to more flexible genes.

We also tested the effect of inclusion of Cas2 on the sequence specificity of EcoCas1, and observed that Cas2 had no effect, with strong preference for a guanine at +1 still observed.

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Similar(50)

Galapagos sharks are considered to be a circumtropical species with strong preferences for warm, clear waters near reef systems or oceanic islands and generally over continental shelf areas.

Educated affluent white males with strong preferences for nuclear energy disproportionately were knowledgeable.

Species with strong preferences for early or late successional stages after fire may be extinction prone under current fire regimes.

In PlankTOM5, competition and predation between micro- and meso-zooplankton along with strong preferences for nanophytoplankton and diatoms, respectively, leads to their mutual exclusion with a mixture of bottom-up and top-down control of the plankton community composition.

These approaches are based on two well-known stochastic techniques, Markov chains and genetic algorithms, and they aim to automatically detect LS, taking into account that, as pointed out by Felder [19], LS can be changed over time in an unexpected and unpredictable way, and even learners with strong preferences for a specific LS can act, sometimes, in a different way.

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