Submitting an appeal regarding an editorial decision may require a significant investment of time and effort from authors. Therefore, it is important to understand what an appeal entails before making the decision on whether to appeal.

SciSciGPT is an open-source prototype AI collaborator that explores the use of LLM research tools to automate workflows, support diverse analytical approaches and enhance reproducibility in the domain of science of science.

PropMolFlow is a flow-matching method for property-guided molecule generation that matches diffusion model performance while generating stable, valid structures more quickly and enabling the discovery of molecules with under-represented property values.

After years of progress, density functional theory is entering a period of rapid advancement, enabled by emerging generalized schemes, richer descriptors, machine learning, and the anticipated development of broader, higher-quality datasets.

The authors demonstrate that the accuracy of predictions in network biology scales with larger foundation models pretrained with larger, more diverse data and that quantization enables resource-efficient predictions while preserving biological knowledge.

HorusEye is a foundation model for universal X-ray tomography restoration that learns realistic degradation directly from data. It supports imaging at substantially lower doses and reduces hardware requirements while improving expert analysis and downstream AI performance.

InstructNA leverages nucleic acid large language models with HT-SELEX for de novo generation of functional nucleic acids, exhibiting high efficiency and general applicability in designing aptamers for various targets.

This study introduces a unified framework for brain MRI tissue segmentation and region parcellation across the lifespan, demonstrating robust and consistent performance across heterogeneous datasets using a single model.

PoTS is an automated pipeline that maps reaction transition states inside zeolite pores. By identifying hundreds of confined transition states across many frameworks, it explains differences in catalytic selectivity and informs zeolite design.

The authors propose the TANGO reward function, which enables the generation of property-optimized small molecules with predicted synthesis routes, incorporating a small set of shared precursors.

After years of progress, density functional theory is entering a period of rapid advancement, enabled by emerging generalized schemes, richer descriptors, machine learning, and the anticipated development of broader, higher-quality datasets.

Submitting an appeal regarding an editorial decision may require a significant investment of time and effort from authors. Therefore, it is important to understand what an appeal entails before making the decision on whether to appeal.

We highlight some of our favorite cover suggestions from 2025.

Large-scale cooperation is characterized by complex interaction patterns with nonlinear outcomes. Deepening our understanding may be critical to addressing real-world collective challenges.

We celebrate the fifth anniversary of Nature Computational Science and reflect on how we have engaged with the research community.

Digital twins are evolving into self-learning, autonomous systems that link models, data and human interaction. Realizing their full potential depends on interoperability, standardization and the integration of artificial intelligence and advanced computational reasoning across sectors.