Nature Computational Science

Nature Computational Science is a multidisciplinary journal that focuses on the development and use of computational techniques and mathematical models, as well as their application to address complex problems across a range of scientific disciplines. The journal publishes both fundamental and applied research, from groundbreaking algorithms, tools and frameworks that notably help to advance scientific research, to methodologies that use computing capabilities in novel ways to find new insights and solve challenging real-world problems. By doing so, the journal creates a unique environment to bring together different disciplines to discuss the latest advances in computational science.   Disciplines covered by Nature Computational Science include, but are not limited to:

• Bioinformatics
• Cheminformatics
• Geoinformatics
• Climate Modeling and Simulation
• Computational Physics and Cosmology
• Applied Math
• Materials Science
• Urban Science and Technology
• Scientific Computing
• Methods, Tools and Platforms for Computational Science
• Visualization and Virtual Reality for Computational Science

Nature Computational Science is committed to publishing significant, high-quality research through a fair and rigorous peer-review process that is overseen by a team of full-time professional editors.

Flow matching for fast, multi-purpose structure-based ligand generation for drug discovery

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Elevating universal interatomic potentials with large-scale off-equilibrium data

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The Open Materials 2024 (OMat24) inorganic materials dataset and models

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Supporting early-career researchers in peer review

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Protein language models for structural biology

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FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation

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AI and the democratization of knowledge work

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Modeling context-dependent RNA splicing by deep learning

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