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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://neuronalarchitects.com/index.html
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 17, 2016. A C#.NET/C++.NET 4.0 API multi-threaded, parallel class library with CUDA kernels for EEG predictive analytics gleaned from the ModelMaker 2 application. This web service and component library offers functionality to do univariate and multivariate nonlinear time series and frequency based predictive analysis for EEG / Ecog / MEG signals for gaming applications. Neural Maestro works with both EEGLab / BCILab and eConnectome as well as other MATLAB and R packages. It enables one to build highly sophisticated neuroscience applications with little effort in Windows applications.
Proper citation: Neural Maestro (RRID:SCR_001563) Copy
http://bmsr.usc.edu/software/pneuma/
A set of modules that are used to simulate the autoregulation of the cardiovascular and respiratory systems under conditions of changing sleep-wake state and a variety of physiological and pharmacological interventions. It models the dynamic interactions that take place among the various component mechanisms, including those involved in the chemical control of breathing, heart rate, and blood pressure, as well as the effects of changes in the sleep-wake state and arousal from sleep. PNEUMA includes the autonomic control of the cardiovascular system, chemoreflex and state-related control of breath-to-breath ventilation, state-related and chemoreflex control of upper airway potency, as well as respiratory and circulatory mechanics. The model is capable of simulating the cardiorespiratory responses to sleep onset, arousal, continuous positive airway pressure, the administration of inhaled carbon dioxide and oxygen, Valsalva and Mueller maneuvers, and Cheyne-Stokes respiration during sleep. In PNEUMA 3.0, we have extended the existing integrative model of respiratory, cardiovascular, and sleepwake state control, to incorporate a sub-model of glucoseinsulinfatty acid regulation. The extended model is capable of simulating the metabolic control of glucoseinsulin dynamics and its interactions with the autonomic nervous system. The interactions between autonomic and metabolic control include the circadian regulation of epinephrine secretion, epinephrine regulation on dynamic fluctuations in glucose and free fatty acids in plasma, metabolic coupling among tissues and organs mediated by insulin and epinephrine, as well as the effect of insulin on peripheral vascular sympathetic activity. This extended model represents a starting point from which further in silico investigations into the interaction between the autonomic nervous system and the metabolic control system can proceed. Features in PNEUMA 3.0 * Incorporates metabolic component based on prior models of glucose-insulin regulation and free fatty acid (FFA) regulation. * Changes in sympathetic activity from the autonomic portion of PNEUMA produce changes in epinephrine output, which in turn affects the metabolic sub-model. * Inputs from the dietary intake of glucose and external interventions, such as insulin injections, have also been incorporated. * Also incorporated is autonomic feedback from the metabolic component to the rest of PNEUMA: changes in insulin level lead to changes in sympathetic tone. System Requirements: PNEUMA requires Matlab R2007b or higher with the accompanying version of Simulink to be installed on your computer.
Proper citation: PNEUMA (RRID:SCR_001391) Copy
http://www.semantic-measures-library.org
Open source Java library dedicated to semantic measures computation and analysis. Tools based on the SML are also provided through the SML-Toolkit, a command line software giving access to some of the functionalities of the library. The SML and the toolkit can be used to compute semantic similarity and semantic relatedness between semantic elements (e.g. concepts, terms) or entities semantically characterized (e.g. entities defined in a semantic graph, documents annotated by concepts defined in an ontology).
Proper citation: Semantic Measures Library (RRID:SCR_001383) Copy
http://www.farsight-toolkit.org/wiki/FARSIGHT_Toolkit
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. A collection of software modules for image data handling, pre-processing, segmentation, inspection, editing, post-processing, and secondary analysis. These modules can be scripted to accomplish a variety of automated image analysis tasks. All of the modules are written in accordance with software practices of the Insight Toolkit Community. Importantly, all modules are accessible through the Python scripting language which allows users to create scripts to accomplish sophisticated associative image analysis tasks over multi-dimensional microscopy image data. This language works on most computing platforms, providing a high degree of platform independence. Another important design principle is the use of standardized XML file formats for data interchange between modules.
Proper citation: Farsight Toolkit (RRID:SCR_001728) Copy
http://www.genabel.org/packages/GenABEL
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. R software library for genome-wide association analysis for quantitative, binary and time-till-event traits.
Proper citation: GenABEL (RRID:SCR_001842) Copy
http://www.uniklinik-freiburg.de/mr/live/arbeitsgruppen/diffusion/fibertools_en.html
Implemented under MATLAB, this DTI image processing toolbox provides import-filters for several MR file standards, a processing unit to calculate the diffusion tensors; several GUI based tools to calculate fiber tracks and to evaluate the DTI dataset. The results can be filed as images with 3D impression or can be logged in formatted ASCII files. Tools and features: * DTI Processing Unit: Calculates the diffusion tensors and their eigenvalues and eigenvectors. Different file formats are supported (like DICOM, Bruker, binary files, Matlab structures). The standard SIEMENS and GE diffusion encoding schemes are supported; other schemes have to be defined in a separate text, .m or .mat file. * FiberTracking: ** Fiber tracking is realized by using the FACT algorithm (Mori et al., Annal. Neurol 1999). ** Probabilistic tracking realized by using the PiCo (Parker et al., JMRI 2003) approach but with DTI data as basis. It is possible to extract pathways between two seeds by combining two maps (Kreher et al., NeuroImage 2008). ** Global Fiber Tracking on basis of HARDI or DTI data. The method is based on the approach reported in (Marco Reisert et al: Global fiber reconstruction becomes practical. NeuroImage 54(2):955-62) * FiberViewer: ** Visualization and Navigation through different data modalities like DTI maps, fiber tracks, diffusion main directions. ** Supports different kinds of DTI maps (e.g. FA, Trace, lambda images ) ** Creation and manipulation of mask based ROIs. ** Selection of streamline fibers ** Visualization of probabilistic fiber tracking results ** Documentation by logging statistics of ROIs and fiber tracks into text files. ** Import/Export from/to ANALYZE or Nifti * 3D Visualizer: Visualization of map slices, ROIs, and fiber tracks with 3D impression. * Batch Editor: Automatic processing of high amounts of data. Possibility to link processing with SPM8 easily.
Proper citation: DTI and Fibertools Software Package (RRID:SCR_001641) Copy
Issue
http://www.nitrc.org/projects/plink
Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
Proper citation: PLINK (RRID:SCR_001757) Copy
https://adaptivedisclosure.wordpress.com/aida/
A generic set of components that can perform a variety of tasks, such as learn new pattern recognition models, perform specialized search on resource collections, and store knowledge in a repository. W3C standards are used to make data accessible and manageable with semantic web technologies such as OWL, RDF(S), and SKOS. The AIDA Toolkit is directed at groups of knowledge workers that cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. The server offers services for: text indexing and statistics, metadata storage and querying, thesaurus reasoning, annotation, text retrieval, spelling correction, synonym detection, and model learning.
Proper citation: AIDA Toolkit (RRID:SCR_005914) Copy
http://bioinformatics.charite.de/voronoia/
Voronoia is a program suite to analyse and visualize the atomic packing of protein structures. It is based on the Voronoi Cell method and can be used to estimate the quality of a protein structure, e.g. by comparing the packing density of buried atoms to a reference data set or by highlighting protein regions with large packing defects. Voronoia is also targeted to detect locations of putative internal water or binding sites for ligands. Accordingly, Voronoia is beneficial for a broad range of protein structure approaches. It is applicable as a standalone version coming with a user friendly GUI or, alternatively, as a Pymol Plugin. Finally, Voronoia is also available as an easy to use webtool to process user defined PDB-files or to asses precalculated packing files from DOPP, the regularly updated Dictionary of Packing in Proteins.
Proper citation: Voronoia (RRID:SCR_006005) Copy
http://bishopw.loni.ucla.edu/AIR5/
A tool for automated registration of 3D (and 2D) images within and across subjects and within and sometimes across imaging modalities. The AIR library can easily incorporate automated image registration into site specific programs adapted to your particular needs.
Proper citation: Automated Image Registration (RRID:SCR_005944) Copy
http://web.mit.edu/swg/software.htm
Toolbox for post-processing fMRI data. Includes software for comprehensive analysis of sources of artifacts in timeseries data including spiking and motion. Most compatible with SPM processing, but adaptable for FSL as well. * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE
Proper citation: Artifact Detection Tools (RRID:SCR_005994) Copy
KNIME (Konstanz Information Miner) is a user-friendly and comprehensive Open-Source data integration, processing, analysis, and exploration platform. KNIME (naim) is a user-friendly graphical workbench for the entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualization and reporting. The open integration platform provides over 1000 modules (nodes), including those of the KNIME community and its extensive partner network. KNIME can be downloaded onto the desktop and used free of charge. KNIME products include additional functionalities such as shared repositories, authentication, remote execution, scheduling, SOA integration and a web user interface as well as world-class support. Robust big data extensions are available for distributed frameworks such as Hadoop. KNIME is used by over 3000 organizations in more than 60 countries. The modular data exploration platform, initially developed at the University of Konstanz, Germany, enables the user to visually create data flows, execute selected analysis steps, and later investigate the results through interactive views on data and models. KNIME is a proven integration platform for tools of numerous vendors due to its open and modular API. The KNIME.com product pipeline includes an Enterprise Server, Cluster Execution, Reporting solutions, and professional KNIME support subscriptions. KNIME.com also offer services such as data analysis, hands-on training and the development of customized components for KNIME.
Proper citation: Knime (RRID:SCR_006164) Copy
General purpose simulation platform developed to support the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, simulations of large networks, and systems-level models. As such, GENESIS, and its version for parallel and networked computers (PGENESIS) was the first broad scale modeling system in computational biology to encourage modelers to develop and share model features and components. User contributed GENESIS models and simulations are available. You may to contribute a model or simulation. Educational tutorials for instruction in both neurobiology and computational methods have been developed. These tutorials and GENESIS are now being widely used in graduate and undergraduate instruction. These uses include full semester courses in computational neuroscience or neural modeling, short intensive courses or workshops, an option for a course project, and short units on computational neuroscience within courses on artificial neural nets. They also have a repository of user-contributed tutorials and materials for use in neuroscience education. If you have course descriptions, syllabi, exercises, tutorials, or short HOWTO documents, please upload them to Education.
Proper citation: General Neural Simulation System (RRID:SCR_006316) Copy
http://www.mevislab.de/index.php?id=6
Modular framework for the development of image processing algorithms and visualization and interaction methods, with a special focus on medical imaging. It includes advanced medical imaging modules for segmentation, registration, volumetry, and quantitative morphological and functional analysis. The platform allows fast integration and testing of new algorithms and the development of application prototypes that can be used in clinical environments. In MeVisLab, individual image processing, visualization and interaction modules can be combined to complex image processing networks using a graphical programming approach. The algorithms can easily be integrated using a modular, platform-independent C++ class library. An abstract, hierarchical definition language allows the design of efficient graphical user interfaces, hiding the complexity of the underlying module network to the end user. JavaScript components can be added to implement dynamic functionality on both the network and the user interface level. MeVisLab is based on the Qt application framework, the OpenInventor 3D visualization toolkit and OpenGL. Several clinical prototypes have been realized on the basis of MeVisLab, including software assistants for neuro-imaging, dynamic image analysis, surgery planning, and vessel analysis. Feature Overview: :- Basic image processing algorithms and advanced medical imaging modules :- Full featured, flexible 2D/3D visualization and interaction tools :- High performance for large datasets :- Modular, expandable C++ image processing library :- Graphical programming of complex, hierarchical module networks :- Object-oriented GUI definition and scripting :- Full scripting functionality using Python and JavaScript :- DICOM support and PACS integration :- Intuitive user interface :- Integrated movie and screenshot generation for demonstration purposes :- Generic integration of the Insight Toolkit (ITK) and the Visualization Toolkit (VTK) :- Cross-platform support for Windows, Linux, and MacOS X :- Available for 64-bit operating systems
Proper citation: Medical Image Processing and Visualization (RRID:SCR_002055) Copy
Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
Proper citation: SAMTOOLS (RRID:SCR_002105) Copy
A toolbox with graphical user interfaces for processing infant brain MR images. Longitudinal (or single-time-point) multimodality (including T1, T2, and FA) (or single-modality) data can be processed using the toolbox. Main functions of the software (step by step) include image preprocessing, brain extraction, tissue segmentation and brain labeling. Linux operating system (64 bit) is required. A workstation or server with memory >8G is recommended for processing many images simutaneously. The graphical user interfaces and overall framework of the software are implemented in MATLAB. The image processing functions are implemented with the combination of C/C++, MATLAB, Perl and Shell languages. Parallelization technologies are used in the software to speed up image processing.
Proper citation: iBEAT (RRID:SCR_002470) Copy
Software Python tool for visualization and interaction with cortical surface representations of neuroimaging data from Freesurfer. It extends Mayavi powerful visualization engine with interface for working with MRI and MEG data. PySurfer offers command-line interface designed to broadly replicate Freesurfer program as well as Python library for writing scripts to explore complex datasets.
Proper citation: PySurfer (RRID:SCR_002524) Copy
http://fmri.wfubmc.edu/software/Bpm
Software toolbox that performs SPM analysis with voxel-wise imaging covariates. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in Matlab with a user-friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely used T-field, has been implemented in the correlation analysis for more accurate results. Requirements: * SPM2 or SPM5 * MATLAB version 6.5 or higher
Proper citation: WFU Biological Parametric Mapping Toolbox (RRID:SCR_002613) Copy
http://www.nitrc.org/projects/peak_nii/
Software toolbox for statistical image clustering, peak detection and data extraction developed to allow the user to have flexibility of clustering their data. Based on your threshold, it will cluster your data and find the peaks within each cluster. Additionally, it has been combined with a data extraction tool that allows one to extract the data from all the scans of the analysis from all the clusters, along with several other extraction options, with a single command.
Proper citation: peak nii (RRID:SCR_002572) Copy
http://www.loni.usc.edu/Software/FFT
Java library used for the execution of discrete Fourier transforms in 1-D, 2-D and 3-D through the implementation of Fast Fourier Transform (FFT) algorithms. * The FFT library has been written in Java for portability across different platforms, integrated into a single jar file for easy implementation. * The FFT library provides forward and backward fast Fourier transforms in 1-D, 2-D and 3-D with an easy-to-use manner. * The FFT requires the length equal to a number with an integer power of two. This library automatically examines the input data and detects the length to prevent improper execution.
Proper citation: FFT Library (RRID:SCR_002698) Copy
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