Elhanan Borenstein

MAAMOUL identifies disease-associated microbial metabolic modules by integrating metagenomic and metabolomic data through a metabolic network framework.

The paper analyzes the canine gut microbiome across 900 dogs to identify factors influencing microbiome composition and develops a metagenomics-based aging clock.

TAGINE optimizes microbiome feature sets using taxonomy-based splitting, reducing features while maintaining accuracy and speed.

This paper introduces PAPRICA, a framework for integrating microbiome multi-omic data by preserving omic-specific properties and phenotype associations, showing improved performance across datasets.

The paper identifies post-translationally modified amino acids (ptmAAs) as age-related plasma metabolites in dogs, linking them to kidney function and dietary factors.

The paper analyzes DNA methylation in dogs to identify age-related patterns, finding that LINE1 transposons show hypomethylation with age, varying by breed size and sex.

The paper develops an epigenetic clock for dogs using DNA methylation data to show that larger breeds age faster and have higher mortality risk.

This paper evaluates interpolation methods for longitudinal microbiome data, finding that K-nearest neighbors performs best but accuracy varies by dataset and time gap.

This paper introduces MintTea, a method for integrating multi-omic microbiome data to identify disease-associated modules, demonstrating its effectiveness across multiple datasets.

The paper introduces POMS, a phylogeny-aware framework for identifying enriched functions in microbiome data, showing improved accuracy over existing methods in simulated and real datasets.

This paper introduces a chemically-controlled DNA binding switch (ciCas9) to enable temporal modulation of Cas9-based effectors, demonstrating its application in base editors and transcriptional activators.

BURRITO is a web tool that visualizes microbiome multi-omic data, linking taxonomic and functional compositions to explore their co-variation.