David Heller

SVIM-asm detects and genotypes six classes of structural variants from haploid and diploid genome assemblies, outperforming existing tools in sensitivity and F1 scores for insertions and deletions.

This paper introduces a method for chromosome-scale haplotype-resolved genome assembly using long reads and long-range data, achieving high accuracy and contiguity in three human genomes.

SVIM detects and characterizes structural variants from long-read sequencing data, outperforming existing tools on simulated and real datasets.

ssHMM identifies sequence-structure motifs for RNA-binding proteins using a hidden Markov model and Gibbs sampling, outperforming existing tools in accuracy and speed.