In an investigation into the effects of drugs on proteins, an active machine learning algorithm chose which sets of experiments to perform and was able to learn an accurate model of the effects after doing only a fraction of the experiments.
Three-dimensional fluorescence imaging of microbial eukaryotes in environmental samples allows accurate automated taxonomic profiling and quantitative data about ultrastructures and interactions of organisms.
Parallel losses of short-wave light sensitivity in diverse bats occurred through independent changes at multiple steps in the conversion of genotype into functional phenotype, including pre-, during, and post-transcription.
An in-depth metagenomic analysis of possibly the most abundant and widespread microbial lineage in the surface ocean teases apart evolutionary processes that maintain its genomic heterogeneity and biogeography.
A computational strategy for extracting representative numerical features from 3D microscopy data enables in-depth quantitative analysis of cell and tissue organization through machine learning-driven data integration and context-guided visualization.