Sentence examples for little robustness from inspiring English sources

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Also, many alternate pathways require only the swapping of two reactions allowing metabolic networks with very little robustness to substitute some of their reactions.

This will yield a highly specific differentiating metabolite, but may show very little robustness; or in other words, it may only be valid under the particular circumstances of the experiment.

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We reasoned that the inclusion of partitions with three or fewer orthologs will add little to the robustness of the present analysis, so we developed a filtering function in our informatics analysis pipeline that removed any ortholog sets that had fewer than four taxa with genes in the ortholog group.

The systems with PSEQ condition however showed little differences in robustness of MK-PP between perturbation in only kinases' concentration and perturbation in kinases + Sig.

What we're really talking about here is not exactly failure, which does always hurt a little, but resilience, and robustness: taking the risk, then learning from it when it doesn't work; pupils becoming "expert learners, not experts".

Also there is little literature on the robustness of the controller when there are uncertainties or external disturbances in the dynamical model of a mobile robot.

This finding has received surprisingly little attention, given the robustness of the photoperiodic modulation and potential functional significance.

In addition, graph segmentation algorithms are generally complex optimization procedures in which little information about community robustness is accessible.

There have been some discussions on robust multi-objective optimization [159, 160, 161, 162, 163, 164], but little research has studied the robustness in decision making, except for measuring attractiveness by a categorical based evaluation technique (MACBETH) [165].

To our experience, this brings little added value as the robustness values are no more comparable because their normalisation depends on time.

Although it is generally accepted that use of remotely sensed data relies on local calibration, little research has evaluated the robustness of relationships when they are applied across different locations.

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