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.

Hybrid modeling for improved structure prediction of large protein complexes

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HDOCK-Multimer: improved structure prediction of large protein complexes by integrating docking and combinatorial assembly

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LLMs predict material properties based on atom types and not atom positions

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HIP: Hessian Interatomic Potentials without derivatives

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Less can be more for predicting properties with large language models

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Photonic circuits become trainable AI hardware

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Steering complex rhythms

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Epidemiological modeling in the age of artificial intelligence

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