Some analysts perform logrank or Cox tests between risk groups, inferring successful validation if statistical significance is 'achieved' in the validation dataset.
Our data can be analysed on a per-year basis, so the observation of a sustained decline in compounds (i.e. less publications on that target) can infer that validation has stalled (data not shown).
Although the results of the first test suggest a good quality of the reconstructed pathway, it is important to note that this suggestion was inferred from the validation of only 13% (36/270) of all annotated genes.
Since a reliable maximum prior for the age of the root node is not available, we first obtained a linearized tree by fixing the age of the root node at one arbitrary time unit (without any internal constraints) with a smoothing parameter of 10 as inferred by cross validation.
The aforementioned marker validation outcomes specifically inferred that 3,042 validated InDel markers revealing 10 54 bp in silico fragment length polymorphism among desi, kabuli and wild accessions have efficiency to be resolved and genotyped even by a simpler cost-effective agarose gel-based assay using numerous chickpea accessions.
The best number of ancestral populations (K) was inferred through cross-validation of 1 to 10 assumed populations.
The SFT estimates inferred from the ANN validation process were in good agreement (R2>0.95) with the "true" SFT data reported for synthetic and field experiments.
In these cases, protein plasticity could be directly inferred and no further validation was required.
From the sequential ratio s and the average sequential running time per event r obtained for each property, it is also possible to infer the theoretical validation time in the maximally-parallel case by computing r×s; this inferred running time is also shown in Table 4, using the sequential run of MrSim as the baseline.
Therefore, the estimated 68% validation rate and inferred 32% false positive are only rough estimates.
For a cross-dataset validation, we further inferred two additional C3NET gene regulatory networks from the DLBCL data sets in [ 25, 27].
