Identification of core T cell network based on immunome interactome.

ABSTRACT:

Background

Data-driven studies on the dynamics of reconstructed protein-protein interaction (PPI) networks facilitate investigation and identification of proteins important for particular processes or diseases and reduces time and costs of experimental verification. Modeling the dynamics of very large PPI networks is computationally costly.

Results

To circumvent this problem, we created a link-weighted human immunome interactome and performed filtering. We reconstructed the immunome interactome and weighed the links using jackknife gene expression correlation of integrated, time course gene expression data. Statistical significance of the links was computed using the Global Statistical Significance (GloSS) filtering algorithm. P-values from GloSS were computed for the integr

SUBMITTER: Teku GN 

PROVIDER: S-EPMC3937033 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature