Sentence examples for microbial community datasets from inspiring English sources

Studies adopting the original LSA technique have shown interesting and novel discoveries for microbial community datasets.

The 5 positive and 5 negative highest absolute LS Scores from associations uniquely found by eLSA in the microbial community dataset.

In addition, we identified genome fragments that derived from an organism deeply branching with respect to Cyanobacteria in a microbial community metagenomic dataset from a subsurface aquifer (Wrighton et al., 2012).

A rarefaction analysis was performed to estimate the coverage of the microbial community in both sequencing datasets; as expected, sequencing data from the GS FLX Titanium platform provides a far more complete view of the underlying community, while the GS FLX sequencing run was not carried out to saturation.

We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified.

Two classes of methods exist for estimating microbial community abundance from metagenomic datasets: composition-based and identity-based methods.

Using the microbial community and gene expression datasets, we demonstrated that eLSA uniquely captures additional time-dependent associations, including local and time-delayed association patterns, when compared to ordinary correlation methods, such as PCC.

We implemented our algorithm in C++ and tested our program (named GeneStitch) on simulated datasets for a single genome and a dataset for an artificial microbial community.

Over the past decade, microbial ecologists have produced the largest ever community datasets.

We also tested it with a dataset from an artificial microbial community and found that we again assembled more complete genes.

The community dataset comprises sequencing reads obtained from an artificial microbial community with 10 mixed lab-cultured species (Morgan et al., 2010).