Microbiome Data Science / AI·ML / Giant Viruses

Frederik Schulz

Discovering new lineages of life and advancing biosecurity through computational biology and machine learning.

DOE Joint Genome Institute / Lawrence Berkeley National Laboratory ✦ Click anywhere to assemble icosahedral capsids Index

I lead the New Lineages of Life Group at Lawrence Berkeley National Laboratory (DOE JGI / LBNL), where we discover novel bacterial, archaeal, and eukaryotic microbes — and the viruses that shape them — hidden in environmental sequence data.

My work pairs machine learning with multi-omics to expand our map of microbial diversity and to build pathogen-agnostic detection systems for biosecurity.

As Biosecurity Lead at DOE JGI, I translate fundamental microbiome research into practical tools for threat detection and characterization.

Publications
100+
h-index
40
Citations
10k+
  • Microbiome Data Science
  • AI/ML in Biology
  • Giant Virus Biology
  • Novel Microbial Diversity
  • Pathogen Detection
  • Biosecurity
02 Selected Work 10 Entries — 2015–2024
  1. 01 Giant virus biology and diversity in the era of genome-resolved metagenomics Comprehensive review synthesizing current understanding of giant virus diversity and evolution. Nature Reviews Microbiology 2022 Review
  2. 02 Massive diversity of giant viruses in global metagenomes Expanded known giant virus diversity 11-fold through global metagenomic analysis. Nature 2020 Publication
  3. 03 Giant viruses with an expanded complement of translation system components Discovery of giant viruses encoding unprecedented translation machinery components. Science 2017 Publication
  4. 04 Hidden diversity of soil giant viruses Revealed extensive diversity of terrestrial giant viruses in soil environments. Nature Communications 2018 Publication
  5. 05 Marine amoebae with cytoplasmic and perinuclear symbionts Characterization of diverse bacterial symbionts in marine protists. ISME Journal 2015 Publication
  6. 06 gvclass Machine-learning classification and phylogenetic placement of giant virus genomes from metagenomic data. GitHub 2024 Tool
  7. 07 symclatron Neural-network classification system for identifying and characterizing microbial symbionts in genomic datasets. GitHub 2024 Tool
  8. 08 nsgtree Neural-network-guided phylogenetic inference for evolutionary analysis of novel microbial lineages. GitHub 2024 Tool
  9. 09 New Lineages of Life Research group discovering novel microbial diversity through large-scale genomics and multi-omics. DOE JGI / LBNL 2023 Group
  10. 10 SampleX AI-powered biological sample analysis for rapid pathogen identification and characterization. AI Startup 2024 Venture