Advanced artificial intelligence approaches are rapidly transforming how biological data are acquired and analyzed.

This primer introduces the elements and best practices of adapting and using language models for biology.

Risks from AI in basic biology research can be addressed with a dual mitigation strategy that comprises basic education in AI ethics and community governance measures that are tailored to the needs of individual research communities.

As scientists avidly use, tinker and build with artificial intelligence tools, best practices begin to emerge.

MiLoPYP is a two-step, dataset-specific contrastive learning-based method for fast and accurate detection and localization of a diverse range of target structures in cryo-electron tomography data, enabling improved in situ structural biology.

Point spread function (PSF) splitting with the ‘Circulator’, which encodes the fluorophore emission band into the PSF, improves the information content of fluorescence microscopy and enables improved super-resolution imaging and single-particle tracking.

Collaborative augmented reconstruction (CAR) is a platform for large-scale reconstruction of neurons and other cells from multi-dimensional imaging datasets. It can be accessed from a variety of devices simultaneously for efficient and accurate reconstruction.

Spacia is a multiple-instance learning model for cell–cell communication (CCC) interference in single-cell resolution spatially resolved transcriptomics data. Spacia can map complex CCCs by modeling cell proximity and CCC-driven gene perturbation.

The authors present a workflow integrating imaging mass cytometry and imaging mass spectrometry to deconvolute metabolic heterogeneity at the single-cell level.

Using single-cell and spatial transcriptomics data, FlowSig provides a unified signaling modeling framework by connecting intercellular communication mediated by ligand–receptor interactions and intracellular gene expression modules.

Biomaterials are revolutionizing organoid development by offering tunable platforms that provide instructive cues, which enhance cell fate transitions, tissue-level functions and reproducibility. These advances are crucial for harnessing the translational potential of organoids.

Early-career scientists shared some of their plans, hopes and dreams about being a principal investigator at the 2024 annual meeting of the International Society for Stem Cell Research.