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We performed heat map and clustering analysis using a subset of named lipid markers in our dataset to help explain the observed patterns from our richness estimators, major lipid class analysis, and PCA.
There is nothing in our dataset to help us to choose between these two alternatives.
As an uncontrolled study, it cannot provide firm evidence that this strategy led to improved outcomes, but it does provide a large dataset to help develop further research questions.
11 Therefore, the aim of this study was to characterise the prevalence and type of multimorbid conditions by socioeconomic status across different age groups, using cross-sectional data from a large, nationally representative primary care dataset, to help inform future prospective studies.
The domain information was used to assess the reliability of each sequence of the initial dataset, to help define protein families according to their architectural coherence, and to assess the level of functional and structural diversification of hemerythrins, hemocyanins, and tyrosinases across the eukaryote lineages.
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The potential for using large datasets to help us understand human society has been the subject of numerous digital humanities projects, as well as special centres devoted to developing these techniques, such as the Stanford University Literary Lab.
Here, we describe the use of the SymAtlas web‐application and the Membrome datasets to help explore trafficking GTPase function.
In this study, we used public genomic and transcriptomic datasets to help us reconstruct metabolic pathways of glycolysis/fermentation and terpenoid biosynthesis.
In Section 3 we describe our application, OpenStreetCab, that leverages on these datasets to help commuters choose the cheapest taxi provider for their journey.
As a result, the startup developed its so-called "Insight Discovery Platform" to enable businesses to automate the discovery process, automatically mapping entire structure and unstructured datasets, to help them solve those problems faster.
One potential is to use additional external datasets to help estimate gene expression levels and their differences for the dataset of the study.
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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