Cameron Martino

This paper integrates microbiomic and metabolomic data to identify microbial and metabolic drivers of CNS autoimmunity in a mouse model of MS.

TEMPTED improves analysis of longitudinal microbiome data by incorporating time as a continuous variable, achieving high accuracy in phenotype classification and identifying microbial markers linked to birth outcomes.

BIRDMAn is a Bayesian framework for differential abundance analysis in microbiome studies, showing improved statistical power and detecting antibiotic effects and cancer classifiers.

Tensor-cell2cell improves cell-cell communication analysis by incorporating cellular context, identifying communication modules linked to diseases like COVID-19 and Autism Spectrum Disorder.

EMPress provides an interactive tool for visualizing phylogenetic trees alongside multi-omic data, enabling exploratory analyses of microbiome and metabolome datasets.

This paper expands the interpretability of human metabolomes by using food-based annotations, increasing the fraction of molecular features understood 7-fold.

The paper introduces Qurro, a tool for interactively visualizing feature rankings and log-ratios in compositional omics data to improve exploratory analysis.