Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
Pattern recognition in imaging data by >300,000 players of a global, online, commercial computer game is combined with deep learning to improve the accuracy of annotation of subcellular protein localization.
Differences in gene expression between individual cells of the same type are measured across batches and used to correct technical artifacts in single-cell RNA-sequencing data.
A new computational approach enables integrative analysis of disparate single-cell RNA–sequencing data sets by identifying shared patterns of variation between cell subpopulations.
Testing 21 different fecal DNA extraction protocols in multiple laboratories results in a standardized protocol with the potential to improve comparability across human gut microbiome studies.
The Microbiome Quality Control project consortium reports outcomes of a baseline study (MBQC) that will guide future improvements in reproducibility of microbiome analyses.
The global effects of epistasis on protein and RNA function are revealed by an unsupervised model of amino acid co-conservation in evolutionary sequence variation.
LFQbench, a software tool to assess the quality of label-free quantitative proteomics analyses, enables developers to benchmark and improve analytic methods.
Sources of error and bias in PCR amplification of microbial samples for 16S rRNA gene sequencing are systematically evaluated, and best-practice recommendations for reliable amplification are made.