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Condensing the omics fog of microbial communities

期刊

TRENDS IN MICROBIOLOGY
卷 21, 期 7, 页码 325-333

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.tim.2013.04.009

关键词

Eco-Systems Biology; function prediction; integrated omics; machine learning; microbial communities; systematic measurements

资金

  1. ATTRACT programme grant [ATTRACT/A09/03]
  2. Aide a la Formation Recherche (AFR) [PRD-2011-1/SR]
  3. Luxembourg National Research Fund (FNR)
  4. Luxembourg Centre for Systems Biomedicine
  5. University of Luxembourg

向作者/读者索取更多资源

Natural microbial communities are ubiquitous, complex, heterogeneous, and dynamic. Here, we argue that the future standard for their study will require systematic omic measurements of spatially and temporally resolved unique samples in line with a discovery-driven planning approach. Resulting datasets will allow the generation of solid hypotheses about causal relationships and, thereby, will facilitate the discovery of previously unknown traits of specific microbial community members. However, to achieve this, solid wet lab, bioinformatic and statistical methodologies are required to have the promises of the emerging field of Eco-Systems Biology come to fruition.

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