Motivation In this era of exponential data growth, minimizer sampling has become a
standard algorithmic technique for rapid genome sequence comparison. This technique …

Processing large data sets has become an essential part of computational genomics.
Greatly increased availability of sequence data from multiple sources has fueled …

Motivation Selecting a subset of k-mers in a string in a local manner is a common task in
bioinformatics tools for speeding up computation. Arguably the most well-known and …

Generating the hash values of short subsequences, called seeds, enables quickly
identifying similarities between genomic sequences by matching seeds with a single lookup …

Motivation Minimizers are methods to sample k-mers from a string, with the guarantee that
similar set of k-mers will be chosen on similar strings. It is parameterized by the k-mer length …

Motivation Sampling k-mers is a ubiquitous task in sequence analysis algorithms. Sampling
schemes such as the often-used random minimizer scheme are particularly appealing as …

Minimizers are ubiquitously used in data structures and algorithms for efficient searching,
mapping, and indexing of high-throughput DNA sequencing data. Minimizer schemes select …

Motivation Sketching is now widely used in bioinformatics to reduce data size and increase
data processing speed. Sketching approaches entice with improved scalability but also carry …

Motivation Pairwise sequence alignment is a heavy computational burden, particularly in the
context of third-generation sequencing technologies. This issue is commonly addressed by …

As the volume of next generation sequencing data increases, an urgent need for algorithms
to efficiently process the data arises. Universal hitting sets (UHS) were recently introduced …