Microbiome research has grown rapidly over the past decade, with a proliferation of new
methods that seek to make sense of large, complex data sets. Here, we survey two of the …

Motivation: Metagenomics is a powerful approach to study genetic content of environmental
samples, which has been strongly promoted by next-generation sequencing technologies …

Motivation We face an increasing flood of genetic sequence data, from diverse sources,
requiring rapid computational analysis. Rapid analysis can be achieved by sampling a …

Alignment-free methods are increasingly used to calculate evolutionary distances between
DNA and protein sequences as a basis of phylogeny reconstruction. Most of these methods …

Seed design is important for sequence similarity search applications such as read mapping
and average nucleotide identity (ANI) estimation. Although k-mers and spaced k-mers are …

Many algorithms for sequence analysis rely on word matching or word statistics. Often, these
approaches can be improved if binary patterns representing match and don't-care positions …

The study of microorganisms is a field of great interest due to their environmental (eg, soil
contamination) and biomedical (eg, parasitic diseases, autism) importance. The advent of …

Alignment-free classification tools have enabled high-throughput processing of sequencing
data in many bioinformatics analysis pipelines primarily due to their computational …

Motivation Genome sequencing projects sometimes uncover more organisms than
expected, especially for complex and/or non-model organisms. It is therefore useful to …

Vectoral and alignment-free approaches to biological sequence representation have been
explored in bioinformatics to efficiently handle big data. Even so, most current methods …