Nicolae Sapoval

Reticulation-Aware Dissimilarities for Phylogenetic Networks

This paper introduces a family of dissimilarity measures for phylogenetic networks that better capture reticulation differences than existing methods.

DIMPLE: A Tree-Guided Divide-and-Conquer Framework for ILS-Aware Phylogenetic Network Inference on Large-Scale Data

DIMPLE infers phylogenetic networks from large-scale data using a divide-and-conquer approach, achieving accurate merging and improved reticulation recovery over existing methods.

Kente: A Graph-based Pangenomic Approach for Horizontal Gene Transfer Detection in Microbiomes

Kente detects horizontal gene transfer in microbiomes using a pangenome graph-based approach, achieving higher precision and reducing false positives in simulated and real human gut metagenomes.

Leveraging spectrum of graph sheaf Laplacian as a genome-architecture-aware measure of microbiome diversity

The paper introduces a new microbiome diversity measure based on graph sheaf Laplacian spectral energy, showing improved discrimination between healthy and IBD gut microbiomes.

Impact of Data Error on Phylogenetic Network Inference from Gene Trees Under the Multispecies Network Coalescent

This study examines how data errors affect phylogenetic network inference and shows that many methods are vulnerable to these errors, leading to unreliable results.

On the consistency of duplication, loss, and deep coalescence gene tree parsimony costs under the multispecies coalescent

This study proves that gene tree parsimony estimators using duplication, loss, and deep coalescence costs are statistically inconsistent under the multispecies coalescent process.

Theoretical and Empirical Performance of Pseudo-likelihood-based Bayesian Inference of Species Trees under the Multispecies Coalescent

This paper evaluates pseudo-likelihood-based Bayesian inference for species tree estimation under the multispecies coalescent, showing theoretical guarantees and empirical performance on synthetic and biological data.

GRNITE: Gene Regulatory Network Inference with Text Embeddings

GRNITE improves gene regulatory network inference by combining text embeddings and graph neural networks, enhancing AUROC and recall across methods.

Intratumor Heterogeneity Through the Lens of Gene Regulatory Networks

The paper analyzes scRNA-seq data to infer clone-specific gene regulatory networks in tumors and shows distinct network architectures and treatment-induced rewiring across cancer types.

Olivar: automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens

Olivar automates variant-aware primer design for tiled amplicon sequencing of pathogens, improving mapping rates and coverage compared to existing methods.

Lightweight taxonomic profiling of long-read metagenomic datasets with Lemur and Magnet

This paper introduces Lemur and Magnet, lightweight tools for accurate taxonomic profiling of long-read metagenomic datasets, showing they run efficiently on laptops.

The Great Deceiver: miR-2392's Hidden Role in Driving SARS-CoV-2 Infection

The paper identifies miR-2392 as a miRNA involved in SARS-CoV-2 infection, showing its role in inflammation, glycolysis, and hypoxia, and develops a miRNA-based therapeutic targeting it.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission

This study analyzes over 7,000 SARS-CoV-2 datasets to reveal genomic diversity, showing iSNVs and small indels drive variation, and highlights implications for qRT-PCR and transmission tracking.

KOMB: Graph-Based Characterization of Genome Dynamics in Microbial Communities

KOMB identifies repetitive and homologous genomic regions in metagenomes using K-core graph decomposition, validated on simulated and real datasets.