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.
We developed CellOT, a tool that integrates optimal transport with input convex neural networks to predict molecular responses of individual cells to various perturbations. By learning a map between the unpaired distributions of unperturbed and perturbed cells, CellOT outperforms current methods and generalizes the inference of treatment outcomes in unobserved cell types and patients.
CellOT combines the benefits of optimal transport and input convex neural architectures to directly learn and uncover maps between control and perturbed cell states at the single-cell level.
A deep learning approach bypasses iterative trials associated with sensorless adaptive optics to compensate for wavefront deformations when imaging biological specimens, enabling improved deep tissue localization microscopy.
Guided sparse factor analysis (GSFA) is a powerful statistical framework to detect changes in gene expression as a result of perturbations in single-cell CRISPR screening.
D-LMBmap is a fully automated pipeline for mesoscale connectomics including deep-learning modules for axon segmentation, brain region segmentation and whole-brain registration. D-LMBmap works accurately across cell types and modalities.
AlteredPQR is a software tool, available as an R package, to infer remodeling of protein functional modules from whole-cell or tissue lysate proteomic measurements.
A Ni2+-modified MspA nanopore construct can unambiguously discriminate the 20 proteogenic amino acids as well as several post-translational modifications.
Droplet-based microfluidics enable rapid mixing with millisecond dead times and allow single-molecule measurements of non-equilibrium binding kinetics on even challenging, strongly adsorptive samples, such as intrinsically disordered proteins.
Modern high-throughput metagenomics is producing hundreds of thousands of metagenome-assembled genomes (MAGs), which is overwhelming traditional sequence-similarity search methods. We present a computational method, skani, that efficiently compares MAGs on a terabyte scale while being robust to the inherent noise in MAGs, enabling larger and more accurate analyses.
skani achieves fast calculation of average nucleotide identity (ANI) between metagenome-assembled genomes (MAGs), with improved robustness against incomplete and fragmented MAGs.
EzMechanism is a tool for automated prediction of the catalytic mechanisms of enzymes using their three-dimensional structures and chemical reactions as input.
veloVI enhances RNA velocity analysis with uncertainty quantification and extensibility by deep generative modeling of gene-specific transcriptional dynamics.
To capture expansive, seamless fields of view from frozen hydrated specimens by cryo-electron tomography, we developed methods for the collection and processing of montage data. This approach enables rapid acquisition of contiguous regions of specimens using a montaged tilt series collection scheme.
We introduce GelMap, a flexible workflow for reporting deformations and anisotropy in expansion microscopy. By intrinsically calibrating the expansion hydrogel using a fluorescent grid that scales with expansion and deforms with anisotropy, GelMap enables the reliable quantification of expansion factors and correction of deformations.
The GelMap workflow adds a fluorescent grid into samples before expansion, allowing for precise determination of expansion factor and subsequent deformation correction in ExM. GelMap works with diverse samples and expansion methods.
Montage parallel array cryo-tomography adopts principles of montage tomography via regular array beam-image-shift montage acquisition and is robust for imaging large fields of view while retaining high-resolution structural information in cryo-electron tomography.
