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NEST is a simulator for large-scale networks of spiking point neuron models (Gewaltig and Diesmann, 2007). Originally, simulations were controlled via the Simulation Language Interpreter (SLI), a built-in scripting facility implementing a language derived from PostScript (Adobe Systems, Inc., 1999). The introduction of PyNEST (Eppler et al., 2008), the Python interface for NEST, enabled users to control simulations using Python. As the majority of NEST users found PyNEST easier to use and to combine with other applications, it immediately displaced SLI as the default NEST interface. However, developing and maintaining PyNEST has become increasingly difficult over time. This is partly because adding new features requires writing low-level C++ code intermixed with calls to the Python/C API, which is unrewarding. Moreover, the Python/C API evolves with each new version of Python, which results in a proliferation of version-dependent code branches. In this contribution we present the re-implementation of PyNEST in the Cython language, a superset of Python that additionally supports the declaration of C/C++ types for variables and class attributes, and provides a convenient foreign function interface (FFI) for invoking C/C++ routines (Behnel et al., 2011). Code generation via Cython allows the production of smaller and more maintainable bindings, including increased compatibility with all supported Python releases without additional burden for NEST developers. Furthermore, this novel approach opens up the possibility to support alternative implementations of the Python language at no cost given a functional Cython back-end for the corresponding implementation, and also enables cross-compilation of Python bindings for embedded systems and supercomputers alike.
Pubmed ID: 24672470 RIS Download
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Global, collaborative effort for neuroscience, medicine and computing to understand brain, its diseases and its computational capabilities. Goal is to obtain access to research, data sources, platforms and infrastructures offered by other organisations, and enabling organizations outside HBP to use HBP platforms to pursue their own research. Coordinating these activities is the responsibility of the European Research Programme.
View all literature mentionsSoftware tool as simulator for spiking neural network models that focuses on dynamics, size and structure of neural systems rather than on exact morphology of individual neurons. Used for any size spiking neurons networks including models of information processing, models of network activity dynamics, models of learning and plasticity.
View all literature mentionsVANO is a Volume image object AnNOtation System for 3D multicolor image stacks, developed by Hanchuan Peng, Fuhui Long, and Gene Myers. VANO provides a well-coordinated way to annotate hundreds or thousands of 3D image objects. It combines 3D views of images and spread sheet neatly, and is just easy to manage 3D segmented image objects. It also lets you incorporate your segmentation priors, and lets you edit your segmentation results! This system has been used in building the first digital nuclei atlases of C. elegans at the post-embryonic stage (joint work with Stuart Kim lab, Stanford Univ), the single-neuron level fruit fly neuronal atlas of late embryos (with Chris Doe lab, Univ of Oregon, HHMI), and the compartment-level of digital map(s) of adult fruit fly brains (several labs at Janelia Farm, HHMI). VANO is cross-platform software. Currently the downloadable versions are for Windows (XP and Vista) and Mac (Intel-chip based, Leopard or Tiger OS). If you need VANO for different systems (such as 64bit or 32bit, Redhat Linux, Ubuntu, etc), you can either compile the software, or send an email to pengh (at) janelia.hhmi.org. VANO is Open-Source. You can download both the source code files and pre-complied versions at the Software Downloads page.
View all literature mentionsOntology of Cerrado wood plant dynamics to represent the set of concepts about the dynamics, that is, changes over time of the wood vegetation structure, of Cerrado. Ccon describes the main parameters used to measure the changes, such as mortality rate and recruitment rate.
View all literature mentionsNEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
View all literature mentionsPortal for scRNA-seq study. Includes dendrogram visualization and clustering of all cells in scRNA-seq study as well as interactive filtered views for cell type, gene and/or donor group.
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