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            "id": "MGYS00002184",
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                "samples-count": 1968,
                "bioproject": "PRJEB19825",
                "accession": "MGYS00002184",
                "is-private": false,
                "last-update": "2018-01-31T09:01:27",
                "secondary-accession": "ERP021896",
                "centre-name": "UCSDMI",
                "public-release-date": null,
                "study-abstract": "Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn's disease, inflammatory bowel disease, and malnutrition. Sequencing and computational technologies however have been a limiting factor in performing dense timeseries analysis of the human microbiome. Here we present the largest human microbiota timeseries analysis to date, covering two individuals at four body sites over 396 timepoints. Results: We find that despite stable differences between body sites and individuals, daily fluctuations in an individual's microbiota appear characteristic. Additionally, only a small fraction of the total within body site microbial communities appears to be present across all time points, suggesting that if a core temporal microbiome exists it is small. Many more taxa appear to be persistent but non-permanent community members. DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and for assessing responses to therapeutic interventions.",
                "study-name": "Moving pictures of the human microbiome",
                "data-origination": "SUBMITTED"
            },
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