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Nature Machine Intelligence, Published online: 28 May 2026; doi:10.1038/s42256-026-01248-2
Human–AI interactions reshape the self and our social networksNature Machine Intelligence, Published online: 27 May 2026; doi:10.1038/s42256-026-01243-7
Han et al. introduce UniAIR, a unified AI framework that predicts mutation effects across diverse immune recognition settings. The approach enables more generalizable modelling of antibody, antigen and T cell receptor interactions.Nature Machine Intelligence, Published online: 25 May 2026; doi:10.1038/s42256-026-01234-8
pUniFind is a large-scale deep learning model for proteomics that unifies peptide–spectrum scoring and open de novo sequencing. Trained on over 100 million spectra, it substantially improves peptide identification and modification discovery.Nature Machine Intelligence, Published online: 21 May 2026; doi:10.1038/s42256-026-01233-9
Long et al. introduce a neural operator method to solve free boundary problems with high precision. The framework shows promise for real-time predictions in clinical applications, particularly in simulating tumour growth.Nature Machine Intelligence, Published online: 21 May 2026; doi:10.1038/s42256-026-01238-4
Free boundary problems, such as modelling glacier melt, are difficult to capture with neural operators. A new framework addresses this challenge by leveraging the mathematical principle of topological conjugacy.Nature Machine Intelligence, Published online: 18 May 2026; doi:10.1038/s42256-026-01246-4
SpecGP enhances fragment ion coverage to enable the prediction of N-glycopeptide structural spectra across diverse collision energies, thereby improving isomer discrimination and boosting identification confidence through rescoring.Nature Machine Intelligence, Published online: 18 May 2026; doi:10.1038/s42256-026-01253-5
Companies, tech workers and researchers are in a frenzy to embed agentic AI into their workflows, locked in a self-imposed race not to fall behind. There must be a better way to make use of AI technology.Nature Machine Intelligence, Published online: 18 May 2026; doi:10.1038/s42256-026-01247-3
Generative artificial intelligence (GenAI) tools are challenging our understanding of plagiarism. How should we deal with plagiarism of ideas if this misbehaviour is increasingly common, and it is extremely difficult to prove when GenAI is involved? Definitions of research misconduct that specifically address the use of GenAI tools are needed.