Paola Bonizzoni

VESPA-SS detects somatic structural variants from long-read sequencing data without requiring read mapping or a high-quality germline reference, achieving high F1 scores on cancer cell lines.

The paper introduces PBML, an algorithm for efficiently detecting long-range shared ancestry tracts in large haplotype panels by filtering short, uninformative matches.

The paper introduces PlasBin-HMF, a method for plasmid binning from short-read assemblies, which outperforms existing methods by preserving explainability.

This study evaluates structural variant callers using long-read sequencing data, showing performance variation based on ground truth, reference genome, and genomic regions.

Pangebin improves plasmid binning in bacterial isolates by using pangenome-assembly graphs to enhance accuracy across different assemblers.

PanSpace is a convolutional neural network-based tool for fast and scalable indexing of bacterial genome databases, reducing disk space and improving query speed.

This paper introduces an assembly-free method to augment pangenome graphs using long reads from new samples, without aligning to a reference or calling variants.

This paper introduces deepSpecas, a deep learning method for differential analysis of alternative splicing events in RNA-seq samples, achieving higher precision with reduced sensitivity.

RecAlign improves recombination-aware sequence-to-graph mapping by using an A* algorithm with haplotype information and a heuristic function, achieving faster and more efficient performance.

The paper introduces pantas, a pangenomic method for detecting and differentially quantifying alternative splicing events using RNA-Seq data, showing competitive accuracy compared to linear reference-based approaches.

This paper introduces a method to construct pangenome graphs by solving an exact cover problem on blocks, showing how different objectives affect graph properties.

The paper investigates how somatic Transformer and sex chromosome karyotype pathways regulate gene expression during Drosophila gonad development, showing their combined and exclusive effects on germ cell development.

ESGq quantifies alternative splicing events across conditions using event splicing graphs, showing consistent results compared to existing tools.

The paper introduces μ-PBWT, a memory-efficient method for haplotype matching, reducing memory usage by up to 25 times and enabling storage of large datasets on a commodity laptop.

The paper develops CouGaR-g, a deep learning tool using FCGR and CNNs for accurate and fast clade assignment of SARS-CoV-2 sequences, achieving 96.29% accuracy on GISAID data.

The paper introduces RecGraph, a tool that extends sequence-to-graph alignment by incorporating recombinations, and evaluates its performance on bacterial pangenome graphs.

The paper presents efficient data structures for storing and querying the positional Burrows-Wheeler Transform (PBWT) to improve memory usage for large haplotype datasets.

SVDSS improves structural variant discovery in hard-to-call regions using long-read sequencing by combining multiple methodologies, outperforming existing methods in repetitive genomic regions.

The paper introduces a method to identify sample-specific strings in long-read sequencing data for comparative genome analysis without read mapping.

Shark removes irrelevant RNA-Seq reads to improve analysis efficiency without affecting results.

The paper introduces SASC, a method for inferring cancer progression from single-cell sequencing data that allows mutation losses, showing high accuracy on simulated and real datasets.

The paper introduces MP3, a similarity measure for tumor phylogenies that handles multiple mutations, and shows it correctly classifies trees on simulated and real data.

MALVIRUS efficiently calls viral variants from sequencing data and generates population SNP catalogs, validated against GISAID data for SARS-CoV-2.

MALVA is a mapping-free genotyping method that efficiently handles multi-allelic SNPs, indels, and high-density variants with high accuracy and speed.

ASGAL aligns RNA-Seq data to a splicing graph to detect novel alternative splicing events, outperforming methods that align to a reference genome.

The paper evaluates whether relaxing the infinite sites assumption improves tumor phylogenies using an ILP-based approach, finding that allowing mutation losses provides better interpretations of real and simulated datasets.

HapCHAT improves haplotype assembly by adapting error thresholds for higher coverage long reads, enhancing accuracy and reducing computational resources.