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In A duty to participate in epidemiology section we describe digital epidemiology as an evolution of traditional epidemiology that includes personal and proprietary digital data alongside formal medical datasets, and consider the risks imposed by re-purposing such data for DE.
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The authors step back from any particular ecological dataset and consider the approaches that are being taken, their likely outcomes and their potential shortfalls.
For the Kefalonia soft-soil dataset, and considering the level of standard deviation bars, a slight positive correlation may be suggested for torsion only (Fig. 10h).
We discuss the differences between the two datasets and consider several hypotheses aimed at reconciling the observed patterns.
BI was implemented with the program Mr.Bayes v3.1.2 [ 59] under a partitioned model (dataset divided into genes), and considering the model of nucleotide substitution estimated with jModelTest.
By doing this, we could normalize the datasets while conserving the clinical meaning and considering the reference range.
The variability of PTRT and WSCV across datasets and considered ROIs is shown in Fig. 1.
Unrelatedness between clones has been a key assumption in much modelling of drug resistance (e.g. [43] [45]) and in data analysis (e.g. [35], [46]) and it is an important question that needs to be definitively proved or disproved, presumably by analysis of a larger dataset and explicitly considering the threat posed by the presence of nulls.
Because they only capture the global geometric structure of dataset and do not consider the local geometric structure information that is very important for target recognition.
Only reads with percentage of similarity over 90% were extracted from the dataset and considered as chloroplast material.
We explore the complementarity of datasets considering the pathogen in its host, the host and human cases in the context of Puumala orthohantavirus infection in Germany.
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