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.
On the cover: a cellular model learned by an artificial neural network. Cover design by Erin Dewalt, based on a concept by Jianzhu Ma, Samson Fong, Michael Yu and Trey Ideker. p290
There was insufficient data to support the claim of unexpected off-target effects due to CRISPR in a paper published in Nature Methods. More work is needed to determine whether such events occur in vivo.
SUSHI is a new method for imaging the extracellular space with high resolution in living brain tissue to reveal insights into the structure and dynamics of the extracellular space.
When asleep, cancer cells can evade chemo. When they wake up, they can cause cancer recurrence. By deciphering dormancy cues, labs explore how to break this cycle.
An extensive evaluation of differential expression methods applied to single-cell expression data, using uniformly processed public data in the new conquer resource.
cellAlign enables quantitative comparisons of expression dynamics within and between single-cell trajectories based on single-cell RNA-seq or mass cytometry data.
CRISPR-based single-cell pooled screens that use linked barcodes suffer from lost sensitivity due to lentiviral template switching. The barcode-free CROP-seq design circumvents this problem.
Mime-seq achieves cell-type specific, methylation-based, microRNA tagging and sequencing to uncover cell-specific microRNomes in C. elegans and Drosophila.
Embedding a deep-learning model in the known structure of cellular systems yields DCell, a ‘visible’ neural network that can be used to mechanistically interpret genotype–phenotype relationships.
