Santiago Sanchez

FAIRyMAGs provides a modular, FAIR-compliant Galaxy pipeline for generating and analyzing metagenome-assembled genomes, improving accessibility and reproducibility in genome-resolved metagenomics.

This study develops a machine learning framework to predict memory requirements for metagenomic assembly, improving efficiency in high-performance computing environments.

This study compares molecular functions and biosynthetic gene clusters in cyanobacterial genomes to identify specializations associated with symbiotic lifestyles.

This paper introduces SanntiS, a machine learning tool for identifying biosynthetic gene clusters in genomic and metagenomic data, and demonstrates its ability to predict a large number of novel BGCs with experimental validation.