Metabolic modeling with Big Data and the gut microbiome

Jaeyun Sung, Vanessa Hale, Annette C. Merkel, Pan Jun Kim, Nicholas Chia*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

29 Citations (Scopus)

Abstract

The recent advances in high-throughput omics technologies have enabled researchers to explore the intricacies of the human microbiome. On the clinical front, the gut microbial community has been the focus of many biomarker-discovery studies. While the recent deluge of high-throughput data in microbiome research has been vastly informative and groundbreaking, we have yet to capture the full potential of omics-based approaches. Realizing the promise of multi-omics data will require integration of disparate omics data, as well as a biologically relevant, mechanistic framework – or metabolic model – on which to overlay these data. Also, a new paradigm for metabolic model evaluation is necessary. Herein, we outline the need for multi-omics data integration, as well as the accompanying challenges. Furthermore, we present a framework for characterizing the ecology of the gut microbiome based on metabolic network modeling.

Original languageEnglish
Pages (from-to)10-15
Number of pages6
JournalApplied and Translational Genomics
Volume10
DOIs
Publication statusPublished - Sept 2016
Externally publishedYes

Scopus Subject Areas

  • Biotechnology
  • Molecular Biology
  • Pharmaceutical Science

User-Defined Keywords

  • Big Data
  • Data integration
  • Gut microbiome
  • Metabolic modeling
  • Microbial community

Fingerprint

Dive into the research topics of 'Metabolic modeling with Big Data and the gut microbiome'. Together they form a unique fingerprint.

Cite this