A Powerful Technique to Study Microbes, Now Easier
Results
Large-scale genomic analyses with machine learning uncover predictive patterns associated with fungal phytopathogenic lifestyles and traits
The Impact of Genome Analyses on Our Understanding of Ammonia-Oxidizing Bacteria*
Targeted and shotgun metagenomic approaches provide different descriptions of dryland soil microbial communities in a manipulated field study
Conserved genomic collinearity as a source of broadly applicable, fast evolving, markers to resolve species complexes: A case study using the lichen-forming genus Peltigera section Polydactylon
Exometabolomics and MSI: deconstructing how cells interact to transform their small molecule environment
Single‐parent expression drives dynamic gene expression complementation in maize hybrids
A complete toolset for the study of Ustilago bromivora and Brachypodium sp. as a fungal-temperate grass pathosystem
Machine learning-based prediction of activity and substrate specificity for OleA enzymes in the thiolase superfamily
A comparative genomics study of 23 Aspergillus species from section Flavi
JGIota: A Biofuel Breakthrough in Anaerobic Fungi with Michelle O'Malley and Tom Lankiewicz
Phylogenomic analysis of 589 metagenome-assembled genomes encompassing all major prokaryotic lineages from the gut of higher termites
