Volume 23 Issue 3, March 2026

As they train the next generation of scientists, some senior researchers share why they find mentoring fun and rewarding.

A pangenome can reveal the spectrum of genome variation within a species. The toolbox for working with pangenomes is filling up.

The new algorithm DECODE transcends the limitations of omics-specific methods, and provides a unified framework for the deconvolution of transcriptomic, proteomic and metabolomic datasets.

We present STORIES, a computational framework for cell trajectory inference from spatial transcriptomics data profiled at several time points. STORIES learns a spatially informed and interpretable model of differentiation that can be used to predict future cell states and regulators of cell fate decisions.

The Carta algorithm infers a differentiation map — including progenitor cell types and transitions between progenitor and terminal cell types — from high-throughput lineage tracing data. Applying Carta to mouse hematopoiesis and embryoid developmental datasets reveals new intermediate progenitors and a secondary origin for a specialized cell type.

Current single-cell metabolomics methods show low sensitivity and limited coverage of small-molecule metabolites. We developed an ion mobility-resolved mass cytometry technology that incorporates selective ion accumulation and cell superposition strategies to deliver high sensitivity and deep coverage, which captured over 5,000 metabolic peaks and about 800 metabolites from individual cells in a high-throughput manner.

We have engineered symmetric RNA scaffolds that allow structure solution of small RNAs via single-particle cryogenic-sample electron microscopy (cryoEM). This method enabled small-molecule ligand placement in experimental maps and revealed the molecular basis for specificity of natural and synthetic RNA aptamers, thus suggesting routes for structure-guided RNA engineering.

We present MultiCell, a geometric deep-learning model capable of predicting multiple types of cell behaviors over time during the dynamic process of embryonic development. MultiCell sets the stage for data-driven quantitative modeling of multicellular developmental dynamics at single-cell precision.

This study introduces an unprecedented resource of thousands of 3D images representing the diversity of an ecologically dominant group of insects: ants. These data were generated using high-throughput synchrotron X-ray microtomography, which opens a pathway to scalable digitization of the vast diversity of invertebrate life.

This Perspective envisions the future of 3DTFM and provides practical guidelines for experimental and computation strategies for its application.

By learning a differentiation potential using an optimal transport-based approach, STORIES models and infers cell fate trajectories using spatiotemporal omics data.

Carta leverages lineage tracing data to infer the optimal trajectory of cell differentiation.

stVCR models and reconstructs single-cell dynamics of cell differentiation, proliferation and migration using time-series spatial transcriptome data.

MaAsLin 3 is a comprehensive and flexible framework for microbiome association studies with expanded toolsets of statistical models, tests and types of inference.

Performing pandemic-scale phylogenetic analysis poses multifaceted challenges. This study develops methods for identifying and accounting for mutation rate variation and recurrent sequence errors, leading to an improved global phylogenetic tree of >2 million severe acute respiratory syndrome coronavirus 2 genomes.

Metient is a statistical framework that infers patterns of metastatic spread and reconstructs cancer migration histories.

An ion mobility-resolved mass cytometry method for single-cell metabolomics enables multidimensional metabolomic profiling. The approach was used to curate a metabolic single-cell atlas containing 45,603 primary liver cells from aging mice.

DECODE is a universal deconvolution framework for both cell types and cell states that can be applied to transcriptomic, proteomic and metabolomic data.

Engineered RNA domains that can adopt two- and fourfold symmetry are shown to be effective scaffolds for structure determination for RNAs otherwise too small for cryoEM.

MultiCell is a deep learning method to capture complex cell dynamics during multicellular development.

AF2BIND is a logistic regression model trained on AlphaFold2 pair features to predict small-molecule binding-site residues in proteins, without multiple sequence alignments, homology models or knowledge of the true ligand. AF2BIND was used to predict binding sites across the AF2-predicted human proteome, finding thousands of potentially new ligandable sites.

Improved red and green indicators for norepinephrine and their characterization are reported. These indicators allow detection of norepinephrine release in awake behaving mice in dual-color fiber photometry and two-photon imaging applications.

This Resource paper presents a global SARS-CoV-2 phylogenetic tree of 4,471,579 high-quality genomes consistently constructed by Viridian, an efficient amplicon-aware assembler.

Antscan is a publicly accessible database of synchrotron X-ray CT images of ants. The database covers almost 800 species from more than 200 genera and is coordinated with genome sequencing projects that will enable integrative analyses.