Ben C. Lambert

This study shows that heatwaves and turbidity affect foraging behavior of sticklebacks, with prolonged warming reducing feeding rates while turbidity increases them, and their interaction has lasting effects.

The paper introduces a Bayesian framework to infer latent infection risk patterns from virus neutralisation assay titration data, revealing higher and more persistent antibody concentrations for EV-D68 compared to other viruses.

The PERL toolkit uses sand fly blood meals to identify leishmaniasis reservoirs by analyzing gene expression patterns in infected and uninfected specimens.

MetaBeeAI extracts structured evidence from biological literature using a modular LLM pipeline with expert validation, improving consistency and reproducibility across studies.

The paper models how adult mosquito emergence affects age distribution and surveillance metrics, showing emergence variability drives age structure heterogeneity.

The paper develops a mathematical model of flavivirus dynamics within mosquitoes, showing that higher viral doses and multiple blood feeds shorten the extrinsic incubation period.

The paper introduces a new metric for insecticide resistance in mosquitoes and quantifies exposure variability in bioassays across Africa.

This paper presents a Bayesian framework and Shiny app for power analysis in melatonin suppression experiments, accounting for individual variability and experimental parameters.

This paper introduces filter inference, a scalable method for estimating NLME model parameters from snapshot time series data, enabling efficient analysis of large datasets.

The paper shows that model selection based on AIC or model averaging can lead to unreliable treatment response predictions due to nonlinear dynamics, and proposes probabilistic averaging as a more reliable approach.

This paper introduces a Monte Carlo method called Contour Monte Carlo to estimate cell population heterogeneity from snapshot data without requiring predefined clusters.

This paper develops a functional data analysis method to improve the generalizability of near-infrared spectral data for mosquito population monitoring across geographic regions.

The paper introduces a novel Markov Chain Monte Carlo method for inverse sensitivity analysis of deterministic biological models, demonstrating its application to several mathematical models.

This paper introduces an agent-based model of kidney branching morphogenesis and uses Bayesian inference to show that growth factor-dependent cell division is essential for branching.