Sentence examples for modules inferred by from inspiring English sources

At any rate, it is interesting to observe the high density of the modules inferred by MCL.

The performance of ENIGMA is tested on two levels by assessing the overlap between the artificial input correlation network and (i) the network of significant correlations obtained in the first step of the ENIGMA algorithm (before clustering, referred to as ENIGMA-N); (ii) the modules inferred by ENIGMA (ENIGMA-M).

The functions of the subnetwork modules were inferred by Gene ontology (GO) enrichment analysis.

However, modules inferred separately from different conditions yield partial overlaps at best, which makes drawing comprehensive biological conclusions difficult.

Here we have performed an in-depth biological validation of the 30% precision module network inferred by LeMoNe.

The intrinsic association relationship between modules 12 and 17 was suggested by their correlation in the organizational structure of coexpression modules (Figure 5) inferred by estimating the partial correlation coefficients of the 27 modules.

In the far field (UK and continental Europe), the effects of the fine Eyjafjallajökull ash deposited on PV-modules can be inferred by considering previous work on the far field distribution of the ash cloud over Europe.

The nature of this possible functional module may be inferred by examining the functional enrichment of the annotated biclusters used to predict this set in each dataset.

Specifically, edges that are inferred by x output modules and y input modules are now counted as y tp and x - y fp in case x ≥ y, or x tp and y - x fn in case x < y.

As in the calculation of the F'-measure used in the clustering optimization procedure (see above), edges that are inferred by multiple modules are counted multiple times, but in the present case, multiply defined edges may also occur in the input network if they overlap between multiple artificial input modules (see Additional file 1 Figure S1 B).

In order to optimize the clustering parameters, the quality of the clustering for a given (ν1, ν2) is assessed by comparing the known input coexpression network (i.e. the network obtained in the first phase of the ENIGMA algorithm) with the output coexpression network inferred by the modules.