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Figure 5 shows that the most abundant bacteria in normal samples were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium (3.9%), and Eubacterium (3.5%).
The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) ≤ 24) were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium (3.9%), and Eubacterium (3.5%).
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Somatic variants were identified after deducting the normal/germline variants observed in the matched normal samples from those observed in the tumor samples.
To test the theory, he and his colleagues analyzed bacteria in fecal samples from lab mice kept in normal 12-hour cycles of light and darkness.
Our objective was to estimate bacterial species-specific sensitivity (Se) and specificity of both BC and mr-PCR tests for detecting bacteria in milk samples from clinical mastitis cases and from apparently normal quarters, using a Bayesian latent class model.
Normal samples are in bold face.
We next sought to identify the potential bacteria in ERH samples from AD patients by PCR.
PCR-free, Two-Color, Digital Detection of Uropathogenic Bacteria in Urine Samples.
He is building the Cellophone, a handset modification that allows it to detect microbes and bacteria in fluid samples.
Test for bacteria in the samples was conducted within 6 h after sampling.
In general, Gram-positive bacteria were more prevalent than Gram-negative bacteria in all samples.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com