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Due to its capacity of interaction with the austenite phase through solute drag and precipitate pinning effects, Nb is an important variable in the production of high-strength low-alloy steel (HSLA).
In our method, the annealing of the oligo- dT -beads with the poligo- dT -beadse RNA bait gave a better flexibility toligo- dT -beadshich helped in obtaining a better capacity of interaction with RNA binding prothens.
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These intra-membrane aggregates will certainly give rise to saturation effects depending e.g. on the capacity of the interaction surface in which the assembling of FPs may take place or on the availability of regulatory proteins (e.g. specific Rab effectors).
This indicates either a lower efficiency in dosage compensation, or that the buffering capacity of gene interaction networks alone can compensate for dosage differences [ 15].
It thus remains an open question, if ZZ/ZW systems in general have evolved similar chromatin-modifying mechanism as in XX/XY systems [ 18], or if the general buffering capacity of protein interaction networks described for unbalanced dosage of autosomal genes in partial aneuploids [ 19, 20] sufficiently counteracts the detrimental effects of dosage differences in the heterogametic sex.
The experiments described above suggest a broad and general capacity for interaction between members of the three families of proteins that are key regulators of the rice immune response.
Such attributes include gene age, tissue specificity of expression, regulatory capacity, sequence length, rate of sequence variation and capacity for interaction.
Besides the influence of both transcription factors on each other's DNA binding capacity, other levels of interaction are hypothesized.
The adaptability of molecular surfaces appears to play a key role for the capacity for interaction.
This was mainly due to the oxygen storage capacity of CeO2, the interaction between Pt and CeO2/Ni, and the relatively small contact and charge transfer resistances.
Decision theater (DT), which enables the combination of visualization and decision modeling capabilities together with human capacity of insight and interaction, is proposed for addressing this challenging problem in the forest sector.
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