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https://www.gnu.org/software/octave/
A high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments. It may also be used as a batch-oriented language. Octave has extensive tools for solving common numerical linear algebra problems, finding the roots of nonlinear equations, functions written in the Octave language, or by using dynamically loaded modules written in C, C++, Fortran, or other languages., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GNU Octave (RRID:SCR_014398) Copy
A software library written to perform vectorized scientific computing and oriented to ease complex modelling tasks such as those typically needed within environmental models, even when involving irregular and heterogeneous data series. The Mastrave project attempts to allow a more effective, quick interoperability between GNU Octave and Matlab users by using a well documented wrap around the main incompatibilities between those computing environments and by promoting a general idiom based on their common, stable syntagms.
Proper citation: Mastrave modelling library (RRID:SCR_014399) Copy
Debian is Linux distribution composed of free and open source software, developed by community supported Debian Project, which was established by Ian Murdock on August 16, 1993.Debian comes with over 59000 packages (precompiled software that is bundled up in nice format for easy installation on your machine), package manager (APT), and other utilities that make it possible to manage thousands of packages on thousands of computers as easily as installing single application.
Proper citation: Debian (RRID:SCR_006638) Copy
A multi-modal multivariate pattern analysis of neuroimaging data in Matlab / GNU Octave. Links to examples, exercises, and information for developers are available on the main page.
Proper citation: CoSMoMVPA (RRID:SCR_014519) Copy
Software for empirical gramians for model reduction of (nonlinear) input-output systems.
Proper citation: Empirical Gramian Framework (RRID:SCR_015043) Copy
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Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
