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
Volume1849
Pagination227-242
Date Published2018
ISSN1940-6029
KeywordsAnimals, Computational Biology, Gene Regulatory Networks, Host Microbial Interactions, Humans, Microbiota, Systems Biology
Abstract

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.

DOI10.1007/978-1-4939-8728-3_15
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