In this article, we introduce some special fuzzy subsets of modules to characterize quasi-Frobenius (QF) rings.
The other TF enrichments were limited to smaller subsets of modules.
We find that, even with small tolerance, thousands of models can be compatible with the data and use ASP's flexibility to further analyze them: we categorize them according to their input output behavior and identify subsets of modules that are interchangeable with respect to the score.
In the latter case, there is an infinite subset of indecomposable modules K i in K all of which have the same Gabriel Roiter measure γ 1 < γ 0. First, assume that K = add K for some module K, let C = τ - K. For any natural number t, we may choose a subset J of I of cardinality t.
Although TIM barrel proteins typically contain only a few βα-hairpin clamps, defining the spatial relationships of the components of a subset of βαβ modules might increase the probability of predicting the packing of adjacent βα-repeats in the structures.
We selected a subset of the modules based on functional annotation.
We discussed only a subset of the modules that we deemed interesting.
The positively correlated subset of this module is enriched for GO biological processes immune response, T cell activation, and lymphocyte activation [Additional file 3: Supplemental Table S1] and include genes expressed in lymphocytes such as Lck, Cd8b1, and Elf1.
In order to find subset of genes (module) that are tightly connected with each other, the distances between all pairs of genes are calculated based on the adjacency matrix A. Afterwards, the computed distance matrix is subjected to a clustering method which results in detecting the modules.
