NetDecoder: A network biology platform that decodes context-specific biological networks and gene activities

Edroaldo Lummertz Da Rocha, Choong Yong Ung, Cordelia D. Mcgehee, Cristina Correia, Hu Li

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


The sequential chain of interactions altering the binary state of a biomolecule represents the 'information flow' within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein-protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes - network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code ( for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets.

Original languageEnglish (US)
Article numbere100
JournalNucleic acids research
Issue number10
StatePublished - Jun 2 2016

ASJC Scopus subject areas

  • Genetics


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