Alexander I. Manolov

This study evaluates four reference-independent pipelines for detecting spreading organisms in metagenomic datasets, finding the coverage-based method most reliable for sensitive pathogen discovery.

AliMarko identifies eukaryotic viruses in metagenomic data using reference mapping, de novo assembly, and HMM, with tools to reduce false positives and visualize results.

Snapper is a high-sensitive algorithm for detecting methylation motifs from Oxford Nanopore reads, showing improved enrichment sensitivity over existing tools and identifying new methylation sites in H. pylori.

The paper analyzes the respiratory tract microbiota in COVID-19 patients to find associations between microbiota composition and disease severity.

The paper introduces GCB, a tool for visualizing and analyzing prokaryote genome variability, identifying regions of high complexity associated with genomic rearrangements and horizontal gene transfer.

The paper annotates the Hirudo medicinalis genome and analyzes salivary transcriptomes of three leech species to identify salivary cell-specific genes and update knowledge on blood-sucking mechanisms.

VERA simulates antibiotic resistance transmission between pathogens and gut microbiota, showing nonlinear dependencies and exponential disease spread with pathogen resistance.

This study uses whole genome sequencing to analyze gut microbiota changes after Helicobacter pylori eradication therapy, finding reduced alpha-diversity, shifts in metabolic potential, and increased antibiotic resistance genes.