Erida Gjini

The paper develops a mechanistic replicator model to link vaginal microbiota composition to Nugent scores and predict bacterial vaginosis with high accuracy.

This study introduces a method that integrates bottleneck size into selection tests for biological diversity data, improving the detection of selection signatures by accounting for sequencing errors and sampling biases.

The paper develops an SIS model for multi-strain epidemics with co-infection on host contact networks, showing that network heterogeneity increases dynamics speed and stabilizes strain coexistence.

This study investigates how spatial drug heterogeneity affects microbial population dynamics in confined environments, showing that spatial arrangement significantly influences population outcomes.

The paper introduces MetaSpread, a Python simulation tool for tumor growth and metastasis, based on a hybrid mathematical model incorporating cellular dynamics and abiotic factors.

The paper develops a spatial SIS model with coinfection and multiple strains to study how spatial structure and host movement affect pathogen dynamics in heterogeneous environments.

The paper develops a framework to quantify fitness differences between two co-invading strains using the replicator equation and applies it to antibiotic-resistant E. coli in the gut microbiota.

The paper infers pairwise bacterial strain interactions from population frequency data across multiple settings using a replicator dynamics framework applied to Streptococcus pneumoniae serotypes.

The paper models the spatial evolution of multi-drug resistance in bacteria under varying drug gradients using a reaction-diffusion system and Price equation framework.

This paper uses a mathematical model to show that optimal antibiotic treatment duration depends on factors like treatment timing, antibiotic efficacy, and infection dynamics, with short or long treatments potentially being beneficial under different conditions.

The paper develops a mathematical model to quantify bacterial fitness dynamics in intracellular infection scenarios, identifying key parameters that influence infection outcomes.