Sentence examples for trivial interactions from inspiring English sources

Exact(3)

Their writing depicts the flux of life as most of us experience it: not splashy scenes of conflict and discord, but quiet, daily, almost trivial interactions through which we come together and grow apart.

Even seemingly trivial interactions can boost mood and increase the sense of belonging.

As pointed in [ 15 ], through network subtraction, the trivial interactions can be removed and detection of differentially represented pathways can be performed.

Similar(57)

In the following analysis, we discarded all SNP pairs if the correlation coefficient between the pairs >0.5 to avoid trivial interaction effects.

Interestingly, for local+PP, a negative correlation is observed between the rank difference and protein similarity, which suggests that the PP method is able to identify non-trivial interactions, where the two interacting proteins are not necessarily similar according to the kernel.

The reason is likely the non-trivial interactions between the autoregressive coefficients with the changing impact functions.

In spite of the preliminary demonstrations, analytical comprehension of the entire process especially on the purview of non-trivial interactions between stochastic phase-transition phenomena of oligonucleotide chains and hierarchical organization of in vivo transport processes remains unknown.

All interfaces differed significantly from the background of all residues in SWISS-PROT, from the group of surface residues, and from internal residues that were not involved in non-trivial interactions.

In employing a quadratic energy functional in the objective of the topology optimization, non-trivial interactions between different points on the structural boundary are introduced, thus favoring a family of shapes with strip-like (or beam) features.

Discretisation of the horizontal pressure gradient force in layered ocean models is a challenging task, with non-trivial interactions between the thermodynamics of the fluid and the geometry of the layers often leading to numerical difficulties.

As these methods typically use secondary structure prediction methods that do not allow pseudoknots, they fail to predict joint structures formed by non-trivial interactions between a pair of RNAs.

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