Reviews & Analysis

Bioluminescent phasor is a new technology for multiplexed, excitation-free imaging at the microscale using luciferase–luciferin pairs. This platform can readily unmix the broad, overlapping emission spectra of bioluminescent reporters, making possible the dynamic tracking of cellular and molecular features over prolonged time periods.

We developed a streamlined approach coupling microfabricated cell culture substrates, 3D single-objective light sheet imaging and artificial intelligence quantifications to characterize the variability of morphologies of small organoids. Arrayed organoids can be imaged in 3D at around 100 organoids per hour.

Adenosine-to-inosine RNA editing is a common post-transcriptional modification, but can be challenging to identify correctly from Illumina data. We show that Oxford Nanopore RNA sequencing, combined with deep learning models, can be used to accurately detect inosine-containing sites in native transcriptomes and to estimate the modification rate of each site.

Determining the functional properties of a protein from its structure is challenging. This study presents an interpretable deep learning model that directly learns function-bearing structural motifs from raw data, allowing accurate mapping of protein binding sites and antibody epitopes onto a protein structure.

Repository-scale analysis of hundreds of millions to billions of mass spectra is a challenging endeavor due to the complexity and volume of associated data. A deep neural network embedding method is presented that enables large-scale investigation of repeatedly observed yet consistently unidentified mass spectra.

New data collection methods enable ab initio protein structure determination by micro-electron diffraction for the first time.

De novo structure generation from tandem mass spectrometry data will advance annotation of unknown metabolomic signals.

This Perspective focuses on experimental techniques developed for circRNA studies, and provides practical guidelines for performing circRNA research.

A repeat-aware pipeline corrects structural assembly errors and polishes assembly sequences in large repeats without overcorrection.

A novel bright near-infrared fluorescent protein inserted into a nanobody enables visualization of native proteins inside living cells and specific manipulation of cell function, including Boolean protein-based operators.

DiMeLo-seq leverages immunotethered DNA methyltransferases with long-read sequencing to map the locations of chromatin proteins in their natural context.

A novel approach to probabilistically align adjacent multiple tissue slices from spatially resolved transcriptomics data provides unprecedented depth for the investigation of tissue architecture and paves the way for new developments in 3D spatial analytics.

Tangram, gimVI and SpaGE outperformed other integration methods for predicting the spatial distributions of RNA transcripts, while Cell2location, SpatialDWLS and RCTD were the top-performing methods for the cell type deconvolution of spots in histological sections.

Neuromechanical simulations enable the study of how interactions between organisms and their physical surroundings give rise to behavior. NeuroMechFly is an open-source neuromechanical model of adult Drosophila, with data-driven morphological biorealism that enables a synergistic cross-talk between computational and experimental neuroscience.

A flexible open-top light-sheet microscope has been developed that can perform deep three-dimensional imaging on all clearing protocols with low and high optical resolution.

Counting of RNA molecules using unique molecular identifiers (UMIs) is ubiquitous in single-cell sequencing. Here, we introduce molecular spikes, a new type of RNA spike-ins with in-built UMIs. These versatile molecular spikes have many uses in experimental and computational method development and routine biological applications.

Two new toolkits that leverage deep-learning approaches can track the positions of multiple animals and estimate poses in different experimental paradigms.

Engineered viral entry combined with single-cell sequencing technology makes it possible to identify specific ligand–receptor interactions in a high-throughput manner.

By providing challenges to the metagenomics community based on complex and realistic metagenome benchmark datasets, CAMI — the community-driven initiative for the Critical Assessment of Metagenome Interpretation — has created a comprehensive assessment of the performance of metagenomics software for common analyses. As part of its second contest, CAMI II, it evaluates ~5,000 submissions from 76 software programs and their different versions.

This Perspective discusses the use of organoid technology, its current limitations and unmet needs in the context of SARS-CoV-2 research.