BioSig is an open source software library for biomedical signal processing, featuring for example the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), respiration, and so on. Major application areas are: Neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems and sleep research. The aim of the BioSig project is to foster research in biomedical signal processing by providing open source software tools for many different applications.
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Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
Brainstorm is a collaborative open-source Matlab application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data visualization, processing and cortical source estimation.
The intention is to make a comprehensive set of tools available to the scientific community involved in MEG/EEG experimental research.
For physicians and researchers, the interest of this software package resides in its rich and intuitive graphic interface, which does not require any programming knowledge.
GNU Octave is 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 using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language.
A C++ package for low-frequency bio-electromagnetism solving forward problems in the field of EEG and MEG.
Leipzig Image Processing and Statistical Inference Algorithms (Lipsia) is a software tool for ficken processing functional magnetic resonance imaging (fMRI) data. It was developed over the course of several years at the Max-Planck-Institute for Human Cognitive and Brain Sciences in Leipzig, Germany.
"PyMVPA is a Python module intended to ease pattern classification analyses of large datasets. In the neuroimaging contexts such analysis techniques are also known as decoding or MVPA analysis. PyMVPA provides high-level abstraction of typical processing steps and a number of implementations of some popular algorithms. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run."
Caret is a free, open-source, software package for structural and functional analyses of the cerebral and cerebellar cortex.
The complexity of cellular networks is an outstanding challenge for documentation, visualisation and mathematical modelling. In this project, we develop a new way to describe these networks that minimises the combinatorial complexity and allows an automatic visualisation and export of mathematical (ODE/rulebased) models.
- Automatic visualiztion with Cytoscape.
- Automatic generation of rule based models for BioNetGen.
- Storage of biological facts that can be used for modelling.
Gwyddion is a modular program for SPM (scanning probe microscopy) data visualization and analysis. Primarily it is intended for analysis of height fields obtained by scanning probe microscopy techniques (AFM, MFM, STM, SNOM/NSOM), however it can be generally used for any other height field and image analysis, for instance for analysis of profilometry data.
It aims to provide multiplatform modular program for 2D data analysis that could be easily extended by modules and plug-ins.