Jarno Alanko

This paper introduces efficient methods to update colored k-mer indexes without rebuilding them from scratch, enabling dynamic maintenance of large genomic collections.

The paper introduces efficient set operations for SBWT-encoded k-mer spectra, enabling memory-efficient processing of large genomic datasets.

KaryoScope annotates genome assemblies at base-pair resolution across multiple feature classes quickly and without alignment, revealing structural variation in centromeres and subtelomeres.

The paper introduces HKS, a method for exact hierarchical k-mer annotation with variable-length queries, achieving high concordance in human genome assemblies.

The paper introduces a Monte Carlo algorithm to efficiently construct and compress distinct k-mer color sets in microbial genome indexing, reducing memory usage and improving performance.

This paper introduces a novel algorithm for approximate local alignment search using k-bounded matching statistics, showing it is as fast and accurate as state-of-the-art tools in bacterial genomics tasks.

This paper develops a machine learning classifier to predict antibiotic resistance in Mycobacterium tuberculosis using genomic data and achieves high accuracy for first-line antibiotics.

This paper introduces finimizers, frequency-bounded minimizers for k-mer sets, to address frequent minimizer issues in indexing, showing improved query times with a prototype implementation.

The paper introduces an algorithm to compute a minimum plain text representation of k-mer sets without repetitions in linear time and evaluates existing heuristics.

Themisto is a scalable k-mer index for pseudoalignment against bacterial genomes, outperforming existing tools in speed, memory use, and recall.

This paper introduces the Spectral Burrows-Wheeler Transform (SBWT) and develops succinct index structures for efficient k-spectrum membership queries in genomic data.

The paper introduces Syotti, a heuristic method for designing DNA baits that outperforms existing methods in speed and coverage efficiency.

The paper introduces Matchtigs, a method to compress kmer sets with a polynomial algorithm and greedy heuristic, achieving significant size reduction and performance improvements in downstream applications.

The paper introduces a pipeline for genomic epidemiology using mixed samples, showing comparable results to colony picks in a nosocomial setting.

The paper introduces BufBOSS, a compressed dynamic de Bruijn graph that improves update efficiency by buffering changes, outperforming existing tools in time, memory, and deletion speed.

The paper introduces a space-efficient framework for variable-order Markov models, reducing memory usage by up to 100 times compared to previous methods.