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Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions.
Rodrigues, Richard R; Shulzhenko, Natalia; Morgun, Andrey.
Afiliação
  • Rodrigues RR; College of Pharmacy, Oregon State University, Corvallis, OR, USA. rodrrich@oregonstate.edu.
  • Shulzhenko N; College of Veterinary Medicine, Oregon State University, Corvallis, OR, USA.
  • Morgun A; College of Pharmacy, Oregon State University, Corvallis, OR, USA. andriy.morgun@oregonstate.edu.
Methods Mol Biol ; 1849: 227-242, 2018.
Article em En | MEDLINE | ID: mdl-30298258
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Biologia de Sistemas / Redes Reguladoras de Genes / Microbiota / Interações entre Hospedeiro e Microrganismos Limite: Animals / Humans Idioma: En Revista: Methods Mol Biol Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biologia Computacional / Biologia de Sistemas / Redes Reguladoras de Genes / Microbiota / Interações entre Hospedeiro e Microrganismos Limite: Animals / Humans Idioma: En Revista: Methods Mol Biol Ano de publicação: 2018 Tipo de documento: Article