A three-letter genetic sequence codes for each amino acid, so it is straightforward to predict the amino acid sequence from the gene.
The motivation for this precondition is that it is straightforward to predict defects for classes that never presented a defect in their lifetime; probably, they will remain with zero defects in the future.
Looking at the phase portrait of the oscillatory regimes for Model 3 (Figure 9), it's straightforward to predict that, starting from the small amplitude limit cycle of short period, an increase in p53 concentration will lead to a shift of the system to the other oscillatory regime.
This means that it cannot be straightforward to predict the functional consequences of variations at particular genomic loci, in different species or even different individuals.
Nevertheless, given that miR-29 has been shown to indirectly downregulate DNMT1, by directly targeting its transactivator Sp1, 38, 47 the expected effect of miR-29a in the transcription of the AHR gene would not be straightforward to predict.
Although the work presented here and elsewhere support the idea that it is straightforward to predict at least one direct target gene for a previously unstudied TFTR, the real challenge is in the determination of the small-molecule ligands that the TFTRs bind to at the C-terminal end.
In addition, since nAChRs are found on both inhibitory and excitatory neurons in different PFC layers, it is not straightforward to predict how action potential firing of PFC output neurons is altered by nAChR stimulation.
However, it is not straightforward to predict whether this "hypoxic effect" would be also observed in other expression systems like S. cerevisiae, as yeasts behave in a different way with regard to their capacity to secrete, to process and to modify proteins in particular cases.
Because many of these genes do not encode metabolic enzymes, it is not straightforward to predict the ensuing change in expression cost from a metabolic model.
For this process, it is straightforward to determine the predicted clone size distribution as a function of the loss/replacement rate, λ, and the effective stem cell number in the crypt, N ([ 10] and supplementary theory).
