Aristeidis Litos

This study uses genomic feature extraction and machine learning to identify environmental adaptations in prokaryotes, revealing gene and ncRNA associations with salinity, temperature, oxygen, and pH preferences.

The paper identifies synchronized codon usage evolution between functionally related genes across bacterial genomes, revealing new functional associations.

This study investigates how microbial communities adapt after coalescence by mixing freshwater and seawater samples in controlled experiments, finding that environmental filtering has a stronger impact than mixing ratios.

The paper uses chemistry-based vectors to analyze untargeted mass spectrometry data and identifies compound classes that differentiate natural biomes.