Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks.

ABSTRACT: Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical "reduced Google matrix" method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure

SUBMITTER: Lages J 

PROVIDER: S-EPMC5784915 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature