Welcome to the "GeneLab Chats" series. In this brief interview style format, GeneLab speaks with authors of GeneLab-enabled publications to better understand the scope of their publication as well as how the GeneLab data system helped enabled their research. Read more information below about the publication highlighted in this series from Dr. Pedro Madrigal, from the European Bioinformatics Institute (EMBL-EBI), formerly at the University of Cambridge where this work was published.
Exposure to the space environment can potentially alter the abundance of some antimicrobial resistance genes in microbes. A recent publication by Dr. Madrigal and colleagues, “Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome,” is based on the reanalysis of several GeneLab datasets (OSD-67, OSD-69, OSD-302, OSD-303, OSD-309, OSD-311, OSD-350) and applies an artificial intelligence method of assessing antibiotic resistance that differs from traditional analysis approaches. Dr. Pedro Madrigal is a Senior Bioinformatician at the EMBL’s European Bioinformatics Institute, a Visiting Researcher at the University of Cambridge, and a member of the Space Omics Topical Team funded by ESA. He also contributes to the GeneLab Multi-omics Analysis Working Group (AWG). GeneLab recently spoke to Dr. Madrigal about this work, which was funded by NASA and highlights how the GeneLab data systems and AWG enabled this reanalysis.