In our opinion, it is helpful to approximately categorize all statistical hypotheses into three categories with respect to their biological interpretability, whereas each category represents a different degree of difficulty to find a biological interpretation for a hypothesis.
That implies that in order to understand a particular method biologically, i.e., one is capable of providing a biological interpretation, one needs to understand the underlying null hypothesis.
It is important to keep in mind that the selected reaction terms must have a biological interpretation, and one approach would therefore be to construct a dictionary with biologically feasible reactions.
In particular, we present a biological interpretation of disease-free and total extinction states.
The challenge from there was to identify the affected molecular mechanisms and achieve a biological interpretation for that cluster.
We assign a biological interpretation to the predicted habitat suitability score, P(hs), which is the probability at-a-point of finding a breeding and/or a wintering ground.
Each one of these three time points we just noted has a biological interpretation.
In order to provide a biological interpretation of our findings, we searched the predicted targets of each relevant miRNA in three different databases; mirbase targets v5, Targetsan v4.2 [28] [30] and Pictar [31].
A biological interpretation of this model is that those viruses with the smallest genome – but still retaining sufficient genomic sequences to replicate – are selected, at every time point in the evolutionary pathway.
PCA defines single genes in the space of component scores, allowing for a biological association of components to groups of genes having the highest absolute scores and thus permitting a biological interpretation of the obtained discrimination.
A biological interpretation of miRNA function in MS is complicated by the fact that most of the miRNA targets are predicted from bioinformatics analysis and are not yet validated in biological studies.
