Lovro Vrček

GnnDebugger: GNN based error correction in De Bruijn Graphs

GnnDebugger uses Graph Neural Networks to correct errors in De Bruijn Graphs, improving genome assembly accuracy for diploid genomes with low coverage.

DipGNNome: Diploid de novo genome assembly with geometric deep learning and beam-search

DipGNNome introduces a deep learning framework for diploid genome assembly using graph neural networks and beam-search, achieving results comparable to state-of-the-art methods.

A Complete Telomere-to-Telomere Diploid Reference Genome for Indian Population

The paper presents a high-quality, gapless diploid reference genome for an Indian population, revealing extensive structural variation and improved performance for genomic analysis in South Asian samples.

Geometric deep learning framework for de novo genome assembly

This paper introduces GNNome, a geometric deep learning framework for de novo genome assembly that improves contiguity compared to existing tools across multiple species.