We present research on the design, development and application of algorithms for DNA sequence analysis, with a focus on environmental DNA (metagenomes). We present an overview and primer on algorithm development for bioinformatics of metagenomes; work on frameshift detection in DNA sequencing data; work on a computational pipeline for the assembly, feature prediction, annotation and analysis of bacterial genomes; work on unsupervised phylogenetic clustering of metagenomic fragments using Markov Chain Monte Carlo methods; and work on estimation of bacterial genome plasticity and diversity, potential improvements to the measures of core and pan-genomes.
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Algorithm development for next generation sequencing-based metagenome analysis