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Multiscale Neuroscience and Systems Biology Simulator
Moose is the core of a modern software platform for the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, large networks, and systems-level processes.
We have moved Github.com. This should be your source for the latest version of the code.
math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
Java class libraries for structural biology development: includes protein format conversion tool, printf-based text formatting, Pred2ary secondary structure prediction, neuralnet library, Hooke-Jeeves global optimizer, and misc. math & statistics.
NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.
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This is a c-library that provides tools for advanced
analysis of electrophysiological data. It features
denoising, unsupervised classification, time-frequency
analysis, phase-space analysis, neural networks, time-warping and
more.
The aim of GUINNEA (Graphical User Interfaced Neural Network Architecture) is to develop a comfortable and high-featured neuralnet simulator which is highly configurable and flexible. It will support many neural nets and visualization features for those
ptsa (pronounced pizza) is a Python module for performing time series analysis. Although it is specifically designed with neural data in mind (EEG, MEG, fMRI, etc...), the code should be applicable to almost any type of time series.
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