iPHoP: A Matchmaker for Phages and their Hosts
Results
Machine learning-based prediction of activity and substrate specificity for OleA enzymes in the thiolase superfamily
Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa
Correlation-based network analysis combined with machine learning techniques highlight the role of the GABA shunt in Brachypodium sylvaticum freezing tolerance
Integrating chromatin conformation information in a self-supervised learning model improves metagenome binning
Learning representations of microbe–metabolite interactions
MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets
De novo Nanopore read quality improvement using deep learning
iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria
Machine Learning Reveals Signatures of Promiscuous Microbial Amidases for Micropollutant Biotransformations
Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes
Cryptic inoviruses revealed as pervasive in bacteria and archaea across Earth’s biomes
