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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://www.nitrc.org/projects/finslerbacktr/
Software provided as a sub-project in the Finsler-tractography module: http://www.nitrc.org/projects/finslertract
Proper citation: Fiber-tracking based on Finsler distance (RRID:SCR_009475) Copy
http://www.nitrc.org/projects/fdrw/
Simple and efficient, this application performs the Weighted False Discovery Rate procedure of Benjamini and Hochberg (1997) to correct for multiple testing. The good think is that you can test virtually any number of p-values (even millions) obtained with any test-statistics for any data set. The bonus is that you can assign a-priori weights to give a better chance to those variables that you deem important. In practice, this procedure is powerful only with a relatively small number of p-values.
Proper citation: False Discovery Rate Weighted (RRID:SCR_009473) Copy
Software application which aims to assign metric distances on the space of anatomical images in Computational Anatomy thereby allowing for the direct comparison and quantization of morphometric changes in shapes. As part of these efforts the Center for Imaging Science at Johns Hopkins University developed techniques to not only compare images, but also to visualize the changes and differences. For additional information please refer to: Faisal Beg, Michael Miller, Alain Trouve, and Laurent Younes. Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. International Journal of Computer Vision, Volume 61, Issue 2; February 2005. M.I. Miller and A. Trouve and L. Younes, On the Metrics and Euler-Lagrange Equations of Computational Anatomy, Annual Review of biomedical Engineering, 4:375-405, 2002. Software developed with support from National Institutes of Health NCRR grant P41 RR15241.
Proper citation: LDDMM (RRID:SCR_009590) Copy
https://www.nitrc.org/projects/gmac_2012/
Open-source software toolbox implemented multivariate spectral Granger Causality Analysis for studying brain connectivity using fMRI data. Available features are: fMRI data importing, network nodes definition, time series preprocessing, multivariate autoregressive modeling, spectral Granger causality indexes estimation, statistical significance assessment using surrogate data, network analysis and visualization of connectivity results. All functions are integrated into a graphical user interface developed in Matlab environment. Dependencies: Matlab, BIOSIG, SPM, MarsBar.
Proper citation: GMAC: A Matlab toolbox for spectral Granger causality analysis of fMRI data (RRID:SCR_009581) Copy
http://www.loni.usc.edu/Software/moreinfo.php?package=BGE
A JAVA application designed to create taxonomies or hierarchies in order to classify and organize information.
Proper citation: BrainGraph Editor (RRID:SCR_009536) Copy
http://www.openbioinformatics.org/annovar/
An efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)
Proper citation: ANNOVAR (RRID:SCR_012821) Copy
http://www.nitrc.org/projects/se_linux/
Software tools optimized for performing univariate and multivariate imaging genetics analyses while providing practical correction strategies for multiple testing. The goal of this project is to merge two important research directions in modern science, genetics and neuroimaging. This entails combining modern statistical genetic methods and quantitative phenotyping performed with high dimensional neuroimaging modalities. So far, however, standard imaging tools are unable to deal with large-scale genetics data, and standard genetics tools, in turn, are unable to accommodate large size and binary format of the image data. Their focus is to create imaging genetics tools for classical genetic and epigenetic epidemiological analyses such as heritability, pleiotropy, quantitative trait loci (QTL) and genome-wide association (GWAS), gene expression, and methylation analyses optimized for traits derived from structural and functional brain imaging data
Proper citation: Solar Eclipse Imaging Genetics tools (RRID:SCR_009645) Copy
http://www.nitrc.org/projects/gppi/
An automated toolbox for a generalized form of psychophysiological interactions for SPM and FSFAST. The automated toolbox can do the following: (a1) produce identical results to the current implementation in SPM (a2) use the current implementation of PPI in SPM but using the regional mean instead of the eigenvariate (a3) use a generalized form that allows a PPI for each task to be in the same model using either the regional mean of eigenvariate (b) create the model using the output of one of the (a) options and the first level design (c) estimate the model (/results directory) (d) compute the contrasts specified.
Proper citation: Generalized PPI Toolbox (RRID:SCR_009489) Copy
http://www.nitrc.org/projects/dcm2nii/
A tool for converting images from the complicated formats used by scanner manufacturers (DICOM, PAR/REC) to the NIfTI format used by various scientific tools. dcm2nii works for all modalities (CT, MRI, PET, SPECT) and sequence types.
Proper citation: dcm2nii (RRID:SCR_014099) Copy
http://www.openbioinformatics.org/gengen/
A suite of free software tools to facilitate the analysis of high-throughput genomics data sets. The package is currently a work-in-progress and infrequently updated.
Proper citation: GenGen (RRID:SCR_013447) Copy
http://www.multifactordimensionalityreduction.org/
Software application that is a data mining strategy for detecting and characterizing nonlinear interactions among discrete attributes (e.g. SNPs, smoking, gender, etc.) that are predictive of a discrete outcome (e.g. case-control status). The MDR software combines attribute selection, attribute construction and classification with cross-validation to provide a powerful approach to modeling interactions. (entry from Genetic Analysis Software)
Proper citation: MDR (RRID:SCR_013427) Copy
http://www.cns.atr.jp/dni/en/downloads/brain-decoder-toolbox/
Software that performs ?decoding? of brain activity, by learning the difference between brain activity patterns among conditions and then classifying the brain activity based on the learning results. BDTB is a set of Matlab functions. BDTB is OS-independent.
Proper citation: Brain Decoder Toolbox (RRID:SCR_013150) Copy
http://www.nitrc.org/projects/dti-denoising/
A Matlab package which contains six denoising filters and a noise estimation method for 4D DWI. The package includes nonlocal means, local PCA and Oracle DCT methods. Based on image redundancy and/or sparsity, the proposed filters provide efficient denoising while preserving fine structures.
Proper citation: DTI denoising (RRID:SCR_014102) Copy
Web application which allows users to visualise and collaboratively segment and annotate any brain MRI dataset available online via URL. A list of brains are available for use on the main site. Segmentations are automatically saved and can be downloaded as Nifti files or triangular meshes. Users can point BrainBox to their own Nifti data, or try data catalogues created by the community.
Proper citation: BrainBox (RRID:SCR_014750) Copy
http://www.nitrc.org/projects/sfmproject/
Structure from motion algorithms repository. Common interface for various sfm algorithms.
Proper citation: SFMProject (RRID:SCR_014166) Copy
http://www.brain-connectivity-toolbox.net
A large selection of complex network measures in Matlab that are increasingly used to characterize structural and functional brain connectivity datasets. Several people have contributed to the toolbox, and if you wish to contribute with a new function or set of functions, please contact Olaf Sporns. All efforts have been made to avoid errors, but users are strongly urged to independently verify the accuracy and suitability of toolbox functions for the chosen application. Please report bugs or substantial improvements.
Proper citation: Brain Connectivity Toolbox (RRID:SCR_004841) Copy
A C++ software framework to develop, simulate and run magnetic resonance sequences on different platforms.
Proper citation: Object-Oriented Development Interface for NMR (RRID:SCR_005974) Copy
http://www.biological-networks.org/p/outliers/
Software that performs a morphology-based approach for the automatic identification of outlier neurons based on neuronal tree structures. This tool was used by Zawadzki et al. (2012), who reported on and its application to the NeuroMorpho database. For the analysis, each neuron is represented by a feature vector composed of 20 measurements, which are projected into lower dimensional space with PCA. Bivariate kernel density estimation is then used to obtain a probability distribution for cells. Cells with high probabilities are understood as archetypes, while those with the small probabilities are classified as outliers. Further details about the method and its application in other domains can be found in Costa et al. (2009) and Echtermeyer et al. (2011). This version requires Matlab (Mathworks Inc, Natick, USA) and allows the user to apply the workflow using a graphical user interface.
Proper citation: DONE: Detection of Outlier NEurons (RRID:SCR_005299) Copy
A Monte Carlo (MC) solver for photon migration in 3D turbid media. Different from existing MC software designed for layered (such as MCML) or voxel-based media (such as MMC or tMCimg), MMC can represent a complex domain using a tetrahedral mesh. This not only greatly improves the accuracy of the solutions when modeling objects with smooth/complex boundaries, but also gives an efficient way to sample the problem domain to use less memory. The current version of MMC support multi-threaded programming and can give a almost proportional speed-up when using multiple CPU cores.
Proper citation: Mesh-based Monte Carlo (MMC) (RRID:SCR_006950) Copy
http://cmic.cs.ucl.ac.uk/mig/index.php?n=Tutorial.NODDImatlab
This MATLAB toolbox implements a data fitting routine for Neurite Orientation Dispersion and Density Imaging (NODDI). NODDI is a new diffusion MRI technique for imaging brain tissue microstructure. Compared to DTI, it has the advantage of providing measures of tissue microstructure that are much more direct and hence more specific. It achieves this by adopting the model-based strategy which relates the signals from diffusion MRI to geometric models of tissue microstructure. In contrast to typical model-based techniques, NODDI is much more clinically feasible and can be acquired on standard MR scanners with an imaging time comparable to DTI.
Proper citation: NODDI Matlab Toolbox (RRID:SCR_006826) Copy
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