Sentence examples for modules of disease from inspiring English sources

If the prioritized genes of a queried phenotype are further divided into sub-groups which are related to subtypes of the disease, then we call each sub-group of genes as the susceptible modules of disease subtypes.

Since disease genes tend to interact with each other [ 1, 2] the choice may be facilitated by searching for modules of disease genes that are co-expressed and interact [ 3, 4].

In this study, we propose a novel computational tool, DrugComboRanker, to prioritize drug combinations for specific cancers by selecting combinations targeting the alternative and complementary signaling modules of disease.

The algorithm assigns a distance value to candidate genes based on a random walk with restart (RWR), which reflects how well candidate genes are connected to modules of disease genes [ 56].

However, the enrichment analysis implemented in the method is based on differentially expressed genes, disease driver genes are not clearly defined, so that drugs targeting the causal dysfunctional signaling modules of disease maybe missed out (Lee et al., 2012).

Since higher network scores signify a smaller global distance to the set of input disease genes, this demonstrates that addition of genes that were predicted on the basis of disease/gene associations supported the network scores of test genes in the vicinity of modules of disease genes.

Network-based analyses of omics data have identified modules of disease-associated genes that have been used to obtain both a systems level and a molecular understanding of disease mechanisms.

While some eQTL analyses of human brain tissue have been recently reported [ 19], eQTL studies have also been combined with network analyses to identify transcription modules of disease-related, co-expressed genes [ 20- 23] and to find causal pathways in glioblastomas [ 24].

We used two state-of-art network clustering approaches [ 25, 26] to identify the modules of diseases-drugs.

On the other hand, the dysfunctional signaling modules of diseases are reconstructed by integrating disease genomics data and protein interactome data.

The Bayesian non-negative matrix factorization with the β-divergence (BNMFβD; Tan and Fevotte, 2013) approach is conducted to partition the drug functional network into connected functional communities, whose targets indicate the inhibited signaling modules of diseases.