...and we love it!
Scroll down to read how we combine
bioinformatics and experimental approaches
to study horizontal gene transfer, antibiotic resistance,
CRISPR-Cas and other fascinating microbial systems.
Metagenomics, Machine learning, Molecular microbiology, and Fun!
We strive to better understand key interaction mechanisms within microbial communities and to promote their application in biotechnology and medicine. By combining state-of-the-art machine learning, molecular biology, and metagenomic techniques, we decipher functions in the nexus of microbial interactions, such as CRISPR-Cas, anti-CRISPRs, antibiotic resistance genes, and bacterial secretion systems.
If you're interested to learn about “reading” microbial genomes using language models, the experiments we conducted in the international space station, or how plasmids protect themselves against systems such as CRISPR-Cas, we invite you to read about our research projects here.
Gene expression during plasmid establishment
Plasmid 2025
Anti-defence systems
in the leading region of plasmids
Nature 2024
Review of NLP approaches in genomics, and proteomics
arXiv 2025
DRAMMA: an ML approach for AMR gene detection
Microbiome 2025
GeNLP: NLP-based exploration of microbial gene
function
Bioinformatics 2024
CRISPR-based genetic
diagnostics in microgravity
Biosens. Bioelectron. 2023
Deciphering microbial gene
function using NLP
Nature Communications 2022
Programmed DNA destruction by miniature CRISPR-Cas14
Science 2018
New CRISPR–Cas systems from metgaenomic data
Nature 2017
Major bacterial lineages are largely devoid of CRISPR-Cas
Nature Communications 2016
Analysis of 38 Legionella spp reveals diverse effectors
Nature Genetics 2016
Modeling the Type-IVB secretion signals
PNAS 2013
Principal Investigator
Research Associate
Ph.D. Student
Ph.D. Student
Ph.D. Student
Ph.D. Student
Ph.D. Student
Ph.D. Student
M.Sc. Student
M.Sc. Student
Data Analyst
Software Specialist
Undergraduate Student
Undergraduate Student
