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<i>Nature Computational Science</i> 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 <i>Nature Computational Science</i> include, but are not limited to: <ul><li>Bioinformatics</li><li>Cheminformatics</li><li>Geoinformatics</li><li>Climate Modeling and Simulation</li><li>Computational Physics and Cosmology</li><li>Applied Math</li><li>Materials Science</li><li>Urban Science and Technology</li><li>Scientific Computing</li><li>Methods, Tools and Platforms for Computational Science</li><li>Visualization and Virtual Reality for Computational Science</li></ul><i>Nature Computational Science</i> 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.

<p><em>Scientific Data</em>&nbsp;is an open access journal dedicated to data, publishing descriptions of research datasets and articles on research data sharing from all areas of natural sciences, medicine, engineering and social sciences. It aims to&nbsp;advance&nbsp;the sharing and reuse of scientific data, promote wider data sharing and reuse, and to credit those that share.</p> <p>Find out more about the key principles that drive&nbsp;<em>Scientific Data</em></p> <p><em>Scientific Data</em>&nbsp;primarily publishes Data Descriptors. These provide&nbsp;detailed descriptions of research datasets, including the methods used to collect the data and technical analyses supporting the quality of the measurements. Data Descriptors focus on helping others reuse data, rather than testing hypotheses, or presenting new interpretations, methods or in-depth analyses.</p> <p><em>Scientific Data</em>&nbsp;also welcomes submissions describing analyses or meta-analyses of existing data, and original articles on systems, technologies and techniques that advance data sharing and reuse to support reproducible research.</p> <p><em>Scientific Data</em>&nbsp;uses a thorough peer-review process that evaluates the rigour and quality of the experiments used to generate the data and the completeness of the description of the data. The actual data are stored in one or more public, community-recognized repositories, and release of the data is verified as a condition of publication.</p> <p>Data Descriptors may describe data from new or published studies, and can be published alongside traditional research works. Data Descriptors that describe previously published datasets should&nbsp;provide new content sufficient to merit further publication: for example, updates to important datasets, fuller release of a dataset, or additional information that aids reuse. Please see our policies on&nbsp;complementary&nbsp;and&nbsp;prior&nbsp;publication.</p>

Nature Sustainability will publish significant original research from a broad range of natural, social and engineering fields about sustainability, its policy dimensions and possible solutions. Understanding how to ensure the well-being of current and future generations within the limits of the natural world is the overarching goal of sustainability research. Nature Sustainability will cover topics including water, air and soil pollution, agriculture and food security, water–energy–land nexus, water-soil-waste nexus and climate change, among many others.

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Analysis at the intersection of money, corruption, and geopolitics based on the latest social science research.

I write the articles I wish I had when I was learning Python programming I learn through narratives, stories. And I communicate in the same way, with a friendly and relaxed tone, clear and accessible

A website dedicated to the fascinating world of mathematics and programming.