Karel Břinda

This paper introduces a Pareto optimization method for masked superstrings to improve the compression of pan-genome k-mer sets, achieving 12-19% better compressibility.

The paper explains why phylogenetic compression works well by introducing a formal framework and showing that Neighbor Joining achieves near-optimal compression under the Infinite Sites Model.

The paper identifies deletion-born gene fusions as a mechanism for novel gene emergence in bacteria, demonstrating their prevalence across the bacterial tree of life.

The paper develops Phylign-Fulgor, a method for efficient k-mer search across millions of bacterial genomes on laptops, improving speed and reducing memory usage compared to existing tools.

This paper introduces FMSI, a superstring-based index for k-mer sets that improves space efficiency and query performance compared to existing methods.

This paper evaluates RASE, a neighbor typing method using long-read sequencing, for predicting sequence types and antimicrobial susceptibility of Klebsiella pneumoniae in real time.

This paper introduces phylogenetic compression to efficiently search large microbial genome collections, achieving significant compression improvements and enabling fast BLAST-like searches on desktop computers.

This paper introduces f-masked superstrings to enable efficient set operations on k-mer sets using index merging and Burrows-Wheeler Transform techniques.

The paper introduces masked superstrings as a unified framework for k-mer set representations, showing they are NP-hard to compute and proposing greedy heuristics for efficient implementation.

The paper introduces simplitigs, a compact and scalable representation of de Bruijn graphs, showing improved efficiency in sequence length and node count, especially with larger datasets.

This paper introduces a method to rapidly infer antibiotic resistance and susceptibility from bacterial genomes using genomic neighbor typing, achieving high sensitivity and specificity within minutes to hours.