Dmitry Meleshko

The paper analyzes microbiomes of three sympatric Arctic sponge species, finding functional convergence and specialization within their symbiotic communities, with shifts linked to temperature changes.

Blackbird improves structural variant detection using synthetic and low-coverage long-reads, achieving comparable performance to high-coverage tools with less data.

cloudrnaSPAdes assembles full-length isoforms from barcoded RNA-seq linked-read data, accurately handling high isoform diversity in simulated and real human data.

Ariadne deconvolves synthetic long read data using assembly graphs to improve taxonomic classification and de novo assembly of complex populations.

The paper benchmarks state-of-the-art viral assembly tools on norovirus metagenome samples, showing they can assemble samples into single contigs without additional preprocessing.

CAMP provides a modular metagenomics analysis system that enables scalable, extensible workflows with integrated data visualization and reporting.

This paper introduces a deep learning framework called Cue for structural variant discovery and genotyping, showing improved performance over existing methods on synthetic and real data.

The paper evaluates metagenomic software tools using realistic datasets, highlighting improvements in assembly and taxon profiling while identifying remaining challenges in virus/archaea detection and reproducibility.

The paper develops a cloud computing infrastructure for petabase-scale sequence alignment, identifying over 105 novel RNA viruses and expanding known species by an order of magnitude.

coronaSPAdes improves RNA viral genome assembly, particularly for coronaviruses, by leveraging viral genome structure knowledge.

This study uses rapid diagnostics and metatranscriptomics to analyze SARS-CoV-2 infection, revealing viral evolution, host responses, and drug interactions in NYC samples.

The paper introduces Novel-X, a method using Linked-Read data to detect novel sequence insertions without whole-genome de novo assembly, outperforming short-read tools and enabling cost-effective large-scale screening.

KrakenLinked improves taxonomic classification of metagenomic linked-reads by combining tree pruning and taxa promotion algorithms, reducing false identifications compared to short reads.

Minerva deconvolves barcoded reads in metagenomics to improve taxonomic assignments and sequence clustering without a reference genome.