A toolkit for ARB to integrate custom databases and externally built phylogenies.

Unlabelled: Researchers are perpetually amassing biological sequence data. The computational approaches employed by ecologists for organizing this data (e.g.

Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis.

Symbiotic bacteria often help their hosts acquire nutrients from their diet, showing trends of co-evolution and independent acquisition by hosts from the same trophic levels. While these trends hint at important roles for biotic factors, the effects of the abiotic environment on symbiotic community composition remain comparably understudied. In this investigation, we examined the influence of abiotic and biotic factors on the gut bacterial communities of fish from different taxa, trophic levels and habitats.

Discovering the unknown: improving detection of novel species and genera from short reads.

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments ("reads") from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted.

Comparison of statistical methods to classify environmental genomic fragments.

"Binning" (or taxonomic classification) of DNA sequence reads is an initial step to analyzing an environmental biological sample. Currently, a homology-based tool, BLAST, is one of the most commonly used tools to label DNA reads, but it is argued that BLAST will quickly lose its classification ability as the genome databases grow. In this paper, we compare the accuracies of a naïve Bayes classifier (NBC) and statistical language model to BLAST for binning reads and demonstrate that NBC obtains good performance for the low cost of computational complexity.

Benchmarking blast accuracy of genus/phyla classification of metagenomic reads.

Metagenomics is the study of environmental samples. Because few tools exist for metagenomic analysis, a natural step has been to utilize the popular homology tool, BLAST, to search for sequence similarity between sample fragments and an administered database. Most biologists use this method today without knowing BLAST's accuracy, especially when a particular taxonomic class is under-represented in the database.