Microbiota, Are You Sick? - mSystems®
The human microbiota correlates closely with the health status of its host. This article analyzes the microbial composition of several subjects under different conditions over time spans that ranged from days to months. Using the Langevin equation as the basis of our mathematical framework to evaluate microbial temporal stability, we proved that stable microbiotas can be distinguished from unstable microbiotas. This initial step will help us to determine how temporal microbiota stability is related to a subject’s health status and to develop a more comprehensive framework that will provide greater insight into this complex system.
Health and Disease Imprinted in the Time Variability of the Human Microbiome
Jose Manuel Martí (http://orcid.org/0000-0002-1902-9749)
Daniel Martínez-Martínez (http://orcid.org/0000-0001-8468-1357)
Teresa Rubio
César Gracia
Manuel Peña
Amparo Latorre
Andrés Moya
Carlos P. Garay
Jack A. Gilbert, University of Chicago, Editor
Published in mSystems® on 21 March 2017
Direct link: http://doi.org/10.1128/mSystems.00144-16
mSystems® publishes preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems® encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems® welcomes submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems® provides streamlined decisions, while carrying on ASM's tradition of rigorous peer review.
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