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http://www.nitrc.org/projects/l-neuron

A program which creates anatomically realistic virtual neurons using the formalism of the Lyndenmayer systems to implement sets of neuroanatomical rules discovered by several research groups. The program algorithms read in experimental data - in the form of statistical distributions - to generate virtual structures. L-Neuron samples the values of the parameters within these statistical distributions in a stochastic (random) fashion during dendritic growth.

Proper citation: L-Neuron (RRID:SCR_014132) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/lwdp/

A lightweight framework for setting up dependency-driven processing pipelines. The tool is essentially a configurable shell script (sh/bash), which can be included in other scripts and primarily provides a small number of utility functions for dependency checking and NFS-safe file locking for cluster processing.

Proper citation: Lightweight Data Pipeline (RRID:SCR_014135) Copy   

•   Source: SciCrunch Registry

http://www.lsm.tugraz.at/csim/

Software tool for simulating heterogeneous networks composed of different model neurons and synapses. CSIM simulates networks containing up to a few thousand neurons and up to the order of 1.000.000 synapses. It is capable of supporting different levels of modeling and has an object oriented design. A user manual is available on the site.

Proper citation: CSIM (RRID:SCR_014256) Copy   

•   Source: SciCrunch Registry

http://www.cse.unr.edu/brain/ncs

A neural simulator which models integrate-and-fire neurons with conductance-based synapses. NCS supports simulations for larger models and also supports real-time neurorobotics applications. Two versions of NCS are available: NCS 5, which is based on CPU cluster; and NCS 6, a multi-box, multi-GPU version. NCS 5 models integrate-and-fire neurons with conductance-based synapses using two clusters: four SUN 4600 machines and 208 Opteron cores. NCS 6 is a neural simulator for heterogeneous clusters of both CPUs and GPUS.

Proper citation: NeoCortical Simulator (RRID:SCR_014257) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/neuritetracer

A set of ImageJ plugins for fully automated measurement of neurite outgrowth in fluorescence microscopy images of cultured neurons. The plugin analyzes fluorescence microscopy images of neurites and nuclei of dissociated cultured neurons. Given user-defined thresholds, the plugin counts neuronal nuclei, and traces and measures neurite length. NeuriteTracer accurately measures neurite outgrowth from cerebellar, DRG and hippocampal neurons.

Proper citation: NeuriteTracer (RRID:SCR_014146) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/bvqxtools

A Matlab-based toolbox initially created for reading, writing, and processing of BrainVoyager (QX) files in Matlab.

Proper citation: NeuroElf (RRID:SCR_014147) Copy   

•   Source: SciCrunch Registry

http://copasi.org/

Software application for simulation and analysis of biochemical network models and their dynamics. COPASI supports models in the SBML standard and can simulate their behavior using ODEs or Gillespies stochastic simulation algorithm. Arbitrary discrete events can be included in such simulations. Models in COPASI are based on reactions that convert a set of species into another set of species. Simulation can be performed either with stochastic kinetics or with differential equations. COPASI also includes various methods of analysis and data visualization.

Proper citation: COPASI (RRID:SCR_014260) Copy   

•   Source: SciCrunch Registry

http://www.cyana.org/wiki/index.php/Main_Page

Software for automated structure calculation of biological macromolecules on basis of conformational constraints from nuclear magnetic resonance. Program for automated NMR protein structure calculation. CYANA requires a sufficient list of assigned chemical shifts and lists of cross-peak positions and columns from 2D, 3D, or4D NOESY spectra in order to calculate the assignment of the NOESY cross-peaks and the 3D structure of the protein in solution.

Proper citation: CYANA (RRID:SCR_014229) Copy   

•   Source: SciCrunch Registry

https://www.bruker.com/products/mr/nmr/nmr-software/software/topspin/overview.html

Software package for NMR spectra acquisition, processing, and data analysis. Features include: deconvolution/spectrum simulation/iteration; comprehensive functionalities for processing, displaying and analyzing one and multi-dimensional spectra; and user customization. A full list of features is available on the website.

Proper citation: TopSpin (RRID:SCR_014227) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/exposition/

An R package for descriptive (i.e., fixed-effects) multivariate analysis with singular value decomposition.

Proper citation: ExPosition Packages (RRID:SCR_014107) Copy   

•   Source: SciCrunch Registry

https://www.cgl.ucsf.edu/home/sparky/

A graphical NMR assignment and integration program for proteins, nucleic acids, and other polymers. Sparky displays NMR spectra, the peaks of which users may pick, assign, and integrate using a graphical interface. Users can work with any number of 2, 3 or 4 dimensional spectra simultaneously. Spectra for input to Sparky can be produced with processing programs NMRPipe, Felix, VNMR, XWinNMR or UXNMR. Output consists of text peak lists showing assignments, chemical shifts, volumes, line widths, etc.

Proper citation: Sparky (RRID:SCR_014228) Copy   

•   Source: SciCrunch Registry

https://svi.nl/HuygensSoftware

A set of fluorescence microscope image processing packages which perform image restoration, interactive analysis, and volume visualization of 2D and 3D multi channel microscopy images or time series. The restoration is based on different deconvolution algorithms, that permit the recovery of objects from images that are degraded by blurring and noise. Tutorials and documentation are available on the website.

Proper citation: Huygens Software (RRID:SCR_014237) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/genr/

An MRI resource which provides age-appropriate images of children. It includes an average, age-appropriate T1-weighted image, constructed from 130 typically developing children ages 6-to-10 and a set of 32 resting-state ICA components. These components were generated from 494 typically developing children, ages 6-to-10 years old, using the MELODIC ICA tool, bootstrapped with 1000 resamples. Both of these resources are described in detail in a manuscript submitted for publication.

Proper citation: Generation R Pediatric MRI Resources (RRID:SCR_014114) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/aca_rc

A large scale functional connectivity data mining software package which enables large-scale seed-based analysis and brain-behavior analysis. It can examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables.

Proper citation: Advanced Connectivity Analysis (ACA) (RRID:SCR_014195) Copy   

•   Source: SciCrunch Registry

http://dbm.neuro.uni-jena.de/vbm/

A collection of extensions to the segmentation algorithm of SPM2, SPM5, and SPM8 to provide voxel-based morphometry. The toolboxes are named according to the SPM version. The software is available to the scientific community under the terms of the GNU General Public License. VBM subpages can be accessed from the VBM website.

Proper citation: VBM toolbox (RRID:SCR_014196) Copy   

•   Source: SciCrunch Registry

http://www.malvern.com/en/products/technology/nanoparticle-tracking-analysis/

Software which utilizes the properties of both light scattering and Brownian motion to obtain the particle size distribution of samples in liquid suspension. The Nanoparticle Tracking Analysis software tracks many particles individually and calculates their hydrodynamic diameters using the Stokes Einstein equation.

Proper citation: Nanoparticle Tracking Analysis (RRID:SCR_014239) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/CrimeStat/about.html

A spatial statistics program which provides tools for crime mapping and analyzing crime incident locations. CrimeStat is organized into five sections: data setup, which arranges and organizes the location data; spatial description, which performs analyses such spatial distribution, spatial autocorrelation, and distance and hot spot analysis; spatial modeling, which performs a number of analyses such as Bayesian journey to crime analysis and space-time analysis; crime travel demand modeling, which detects crime patterns and correlations over time and space; and CrimeStat libraries, which are component objects that include all of the routines that were developed through version 2.0 of the regular CrimeStat program.

Proper citation: CrimeStat (RRID:SCR_014243) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/image_synthesis/

A collection of software tools developed for medical image synthesis of typically magnetic resonance (MR) brain images. The approaches have been used to create computed tomography (CT) images from MR input. The goal of image synthesis is to recover MR images with a desired optimal contrast for further processing by either registration or segmentation.

Proper citation: Image Synthesis Tools (RRID:SCR_014123) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/hdbig/

A collection of software tools for high dimensional brain imaging genomics. These tools are designed to perform comprehensive joint analysis of heterogeneous imaging genomics data. HDBIG-SR is an HDBIG toolkit for sparse regression while HDBIG-SCCA is an HDBIG toolkit for sparse association.

Proper citation: HDBIG (RRID:SCR_014120) Copy   

•   Source: SciCrunch Registry

http://www.jmp.com/en_us/software/jmp.html

Statistical software that uses dynamic graphics rather than tables or graphs to visualize raw data. More specific versions of JMP are available for statistical analyses, clinical work, and genomics. Features include statistical modeling, data cleanup, automation and scripting, and experimental design.

Proper citation: JMP (RRID:SCR_014242) Copy   

•   Source: SciCrunch Registry