Kimon Divaris

This paper introduces BGOB, a deep learning framework for longitudinal microbiome interpolation, improving analysis of microbial community trajectories and revealing disease-related associations.

This paper introduces LP-Micro, a machine learning framework for analyzing longitudinal microbiome data to identify time-varying biomarkers predictive of disease outcomes.

The paper evaluates ten differential expression methods for metatranscriptomics data using real and simulated datasets, finding the logistic-beta test has highest sensitivity and reasonable type I error control.

The paper introduces a BZINB model-based method for integrating microbiome and metabolome data, showing improved accuracy in identifying correlations compared to traditional methods.

This paper constructs a single-cell transcriptome atlas of human oral mucosa in health and periodontitis, identifying a stromal-neutrophil axis regulating tissue immunity.