Knut Reinert

This paper introduces a dynamic and updatable sequence-search index called Dynamic HIBF, which efficiently handles large-scale data updates and outperforms existing methods in speed.

DREAM-Stellar improves local alignment speed and accuracy by using parallel processing and a new prefilter, outperforming existing tools like BLAST.

ganon2 improves metagenomics analysis by providing faster, more accurate taxonomic binning and profiling with smaller reference indices.

Fiora predicts compound mass spectra from single fragmentation events using graph neural networks, outperforming existing methods and enabling faster spectral library expansion.

Mistle improves metaproteomics by efficiently searching predicted spectral libraries, outperforming existing tools in speed and memory usage.

This paper introduces HIBF, a fast and space-efficient data structure for approximate sequence queries, showing significant improvements in speed and resource usage over existing tools.

The paper evaluates metagenomic software tools using realistic datasets, highlighting improvements in assembly and taxon profiling while identifying remaining challenges in virus/archaea detection and reproducibility.

Raptor is a fast and memory-efficient tool for searching large nucleotide sequence collections, outperforming existing tools in speed and memory usage.

Ganon improves metagenomics classification by efficiently indexing and updating large reference sequence sets, increasing read classification and species identification compared to existing tools.

PriSeT is a tool for discovering optimal primer sets for DNA metabarcoding, balancing taxonomic coverage and resolution by analyzing reference sequences.

GenMap computes genome mappability exactly and efficiently, outperforming existing methods and enabling marker gene identification in bacterial strains.

EPIFANY improves protein inference accuracy and efficiency by combining loopy belief propagation with convolution trees, outperforming existing methods on benchmark data.

DREAM-Yara provides an efficient read mapper for large reference databases, reducing index construction time and enabling faster updates.

This paper introduces a mixed integer program to find optimal search schemes for approximate string matching using bidirectional FM-index, significantly improving speed over previous methods.