TitleTranskingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions.
Publication TypeJournal Article
Year of Publication2018
AuthorsRodrigues, RR, Shulzhenko, N, Morgun, A
JournalMethods Mol Biol
Date Published2018
KeywordsAnimals, Computational Biology, Gene Regulatory Networks, Host Microbial Interactions, Humans, Microbiota, Systems Biology

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g., mammals and microbes) using diverse types of data.

Alternate JournalMethods Mol Biol
PubMed ID30298258
PubMed Central IDPMC6557635
Grant ListR01 DK103761 / DK / NIDDK NIH HHS / United States
U01 AI109695 / AI / NIAID NIH HHS / United States