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10.1073/pnas.1423854112 http://scihub22266oqcxt.onion/10.1073/pnas.1423854112 C4460507!4460507!25964341     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Natl+Acad+Sci+U+S+A 2015 ; 112 (22): E2930-8 Nephropedia Template TP {{tp|p=25964341|t=2015. Identifying personal microbiomes using metagenomic codes |pdf=|usr=}}{{25964341}} gab.com Text Identifying personal microbiomes using metagenomic codes JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=25964341 #FOAvip Recent surveys of the microbial communities living on and in the human body?the human microbiome?have revealed strong variation in community membership between individuals. Some of this variation is stable over time, leading to speculation that individuals might possess unique microbial ?fingerprints? that distinguish them from the population. We rigorously evaluated this idea by combining concepts from microbial ecology and computer science. Our results demonstrated that individuals could be uniquely identified among populations of 100s based on their microbiomes alone. In the case of the gut microbiome, >80% of individuals could still be uniquely identified up to a year later?a result that raises potential privacy concerns for subjects enrolled in human microbiome research projects. Twit Text FOAVip Identifying personal microbiomes using metagenomic codes ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=25964341 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25964341 #FOAvip English Wikipedia <ref>{{Cite pmid|25964341}}</ref> Identifying personal microbiomes using metagenomic codes #MMPMID25964341 Franzosa EA; Huang K; Meadow JF; Gevers D; Lemon KP; Bohannan BJM; Huttenhower C Proc Natl Acad Sci U S A 2015[Jun]; 112 (22): E2930-8 PMID25964341show ga Recent surveys of the microbial communities living on and in the human body?the human microbiome?have revealed strong variation in community membership between individuals. Some of this variation is stable over time, leading to speculation that individuals might possess unique microbial ?fingerprints? that distinguish them from the population. We rigorously evaluated this idea by combining concepts from microbial ecology and computer science. Our results demonstrated that individuals could be uniquely identified among populations of 100s based on their microbiomes alone. In the case of the gut microbiome, >80% of individuals could still be uniquely identified up to a year later?a result that raises potential privacy concerns for subjects enrolled in human microbiome research projects. äIdentifying personal microbiomes using metagenomic codes (epmc).pdf DeepDyve Pubget Overpricing