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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.alivelearn.net/xjview8/
A viewing program for Statistical Parametric Mapping (SPM2, SPM5 and SPM8). p-value slider, displays multiple images at a time and can be used to build Region of Interest (ROI) masks. For a given region you can find the anatomical name and search the selected region in online database (wiki, Google scholar and PubMed).
Proper citation: xjView: A Viewing Program For SPM (RRID:SCR_008642) Copy
http://www.loni.usc.edu/Software/BrainParser
Software that uses a novel statistical-learning technique to segment brain regions of interest (ROIs) based on a training set of data and generates 3D MRI volumes. The software comes pre-trained on a provided data set but can be retrained to work with your desired regions of interest.
Proper citation: LONI Brain Parser (RRID:SCR_009572) Copy
http://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Extensions/DTIProcess
A DTI processing and analysis toolkit developed in UNC and University of Utah. Tools in this toolkit include dtiestim, dtiprocess, dtiaverage, fibertrack, fiberprocess, et al..
Proper citation: DTIProcess ToolKit (RRID:SCR_009561) Copy
http://www.nitrc.org/projects/cogicat/
While the traditional temporally concatenated Group ICA (TC-GICA) adopting three steps of PCA reduction, it could result in inconsistent and variable components when different subject orders were used, both for the group- and individual-level results. Such instability can further cause instable and thus unreliable statistical results. Subject Order-Independent Group ICA (SOI-GICA) aims to fix this problem by producing stable and reliable GICA results. For details please see the paper Subject Order-Independent Group ICA (SOI-GICA) for Functional MRI Data Analysis (Zhang et al., 2010, NeuroImage)(http://dx.doi.org/10.1016/j.neuroimage.2010.03.039). MICA is the toolbox inplemented SOI-GICA for convenience of usage.
Proper citation: Subject Order-Independent Group ICA (RRID:SCR_009514) Copy
http://www.sci.utah.edu/cibc/software/map3d.html
A scientific visualization application written to display and edit complex, three-dimensional geometric models and scalar, time-based data associated with those models such as high resolution EEG, MEG, and ECG.
Proper citation: map3d (RRID:SCR_009628) Copy
http://www.nitrc.org/projects/brainmask/
Segmentation of the brain from three-dimensional MR images is a crucial pre-processing step in morphological and volumetric brain studies. BrainMask implements a fully automatic brain segmentation algorithm that uses advanced thresholding with morphology and 3D edge detection algorithms. BrainMask demonstrates high segmentation accuracy. For a representative 26 datasets, the segmentation error averaged 3.4% ������ 1.3% (Mikheev A et al. J Magn Reson Imag 27(6):1235-41;2008). BrainMask includes NNN - a tool based on the algorithm developed by John Sled for correcting the intensity non-uniformity in MR data (Sled JG et al. IEEE Trans Med Imag 17(1):87-97;1998). BrainMask also includes a versatile DICOM wiewer and allows to selectively load and organize DICOM images into 3D and 4D datasets.
Proper citation: BrainMask Volume Processing Tool (RRID:SCR_009538) Copy
http://support.brainvoyager.com/available-tools/52-matlab-tools-bvxqtools.html
A Matlab-based toolbox for the reading, writing, and processing of BrainVoyager (QX) files in Matlab. The toolbox is freely available.
Proper citation: BVQXtools (RRID:SCR_009532) Copy
http://www.connectomeviewer.org/viewer/
A free, open source, cross-platform Python-based software application for visualization and analysis in connectome research. Features of the software include: Connectome File Format including metadata, networks, surfaces, volumes, track files; complex network analysis toolboxes; modular plugin architecture for extensibility; Mayavi2 for 3D Scientific Visualization and Plotting; interactive data manipulation and scripting capabilities; and Neuroimaging and Diffusion in Python libraries.
Proper citation: Connectome Viewer (RRID:SCR_009552) Copy
https://code.google.com/p/clever-sv/
A collection of tools to discover and genotype structural variations in genomes from paired-end sequencing reads. The main software is written in C++ with some auxiliary scripts in Python.
Proper citation: CLEVER Toolkit (RRID:SCR_005255) Copy
Software mining pipeline guided by a Bayesian principle to detect single nucleotide polymorphisms, insertion and deletions by comparing high-throughput pyrosequencing reads with a reference genome of related organisms. This pipeline is extended to identify and visualize large-size structural variations, including insertions, deletions, inversions and translocations.
Proper citation: inGAP (RRID:SCR_005261) Copy
http://www.ridom.de/traceedit/
A cross-platform graphical DNA trace viewer and editor that displays the chromatogram files from Applied Biosystems automated sequencers and files in the Staden SCF format. Incorrect base calls can be edited and saved. TraceEdit is freely available and designed to operate on Windows and UNIX platforms.
Proper citation: Ridom TraceEdit (RRID:SCR_005568) Copy
A sequence aligner software program that is 10-100x faster and simultaneously more accurate than existing tools like BWA, Bowtie2 and SOAP2. It runs on commodity x86 processors, and supports a rich error model that lets it cheaply match reads with more differences from the reference than other tools. This gives SNAP up to 2x lower error rates than existing tools and lets it match larger mutations that they may miss. SNAP also natively reads BAM, FASTQ, or gzipped FASTQ, and natively writes SAM or BAM, with built-in sorting, duplicate marking, and BAM indexing.
Proper citation: Scalable Nucleotide Alignment Program (RRID:SCR_005501) Copy
http://cran.r-project.org/web/packages/aLFQ/
An R-package for estimating absolute protein quantities from label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics data. It supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, quantifying on either MS1-, MS2-levels or spectral counts together with validation algorithms to enable automated data analysis and error estimation. Specifically, they used Monte-carlo cross-validation and bootstrapping for model selection and imputation of proteome-wide absolute protein quantity estimation.
Proper citation: aLFQ (RRID:SCR_005925) Copy
http://www-math.u-strasbg.fr/genpred/spip.php?article3
R software package to study, predict and simulate the diffusion of a signal through a temporal gene network. It predicts changes in gene expressions after a biological perturbation in the network and provides graphical outputs that allow monitoring the spread of a signal through the network., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Cascade (RRID:SCR_005861) Copy
https://github.com/dsturg/Spanki
A set of tools to facilitate analysis of alternative splicing from RNA-SEQ data.
Proper citation: Spanki (RRID:SCR_004469) Copy
http://cran.r-project.org/web/packages/kdetrees/
R package using a non-parametric method for estimating distributions of phylogenetic trees, with the goal of identifying trees that are significantly different from the rest of the trees in the sample.
Proper citation: Kdetrees (RRID:SCR_004522) Copy
TrackVis is software tool that can visualize and analyze fiber track data from diffusion MR imaging (DTI/DSI/HARDI/Q-Ball) tractography. It does NOT perform actual fiber tracking. Diffusion Toolkit is a set of tools that reconstruct diffusion imaging data and generate fiber track data for TrackVis to visualize. Because these two sets of tools were developed and maintained separately and each has distinguished funtionalities, they decided to distribute them as two separate programs for the ease of maintenance and upgrade. You do need both of them to perform complete diffusion data processing and analysis. Features of TrackVis include: * Cross-platform. Works on Windows, Mac OS X and Linux with native look and feel. * A variety of track filters (track selecting methods) allowing users to explore and locate specific bundles with ease. * Multiple rendering modes with customizable scalar-driven color codes. * Real-time parameter adjustment and 3D render. * Open format of the track data file allowing users to integrate customized scalar data into the track file and visualize and analyze it. Save and restore scenes in XML style scene file. * Statistical scalar analysis of tracks and ROIs. * Synchronized real-time multiple dataset analysis and display allowing time-point and/or subject comparison. Synchronized analysis and display on same dataset can also be performed in real-time remotely over the network. * Upfront in-line parameter adjustment in real-time. No tedious pop-up dialogs. TrackVis works with Track File created by Diffusion Toolkit. Diffusion Toolkit processes raw DICOM, Nifti format and ANALYZE images. TrackVis and Diffusion Toolkit are cross-platform software. They can run on Windows XP, Mac OS X as well as Linux.
Proper citation: TrackVis (RRID:SCR_004817) Copy
http://www3a.biotec.or.th/c-mii/
A software tool for plant miRNA and target identification. C-mii pipelines are based on combined steps and criteria from previous studies and also incorporated with several tools such as standalone BLAST and UNAFold and pre-installed databases including miRBase, UniProt, and Rfam. C-mii provides following distinguished features. First, it comes with graphical user interfaces of well-defined pipelines for both miRNA and target identifications with reliable results. Second, it provides a set of filters allowing users to reduce the number of results corresponding to the recently proposed constraints in plant miRNA and target biogenesis. Third, it extends the standard computational steps of miRNA target identification with miRNA-target folding module and GO annotation. Fourth, it supplies the bird eye views of the identification results with info-graphics and grouping information. Fifth, it provides helper functions for database update and auto-recovery to ease system usage and maintenance. Finally, it supports the multi-project and multi-thread management to improve the computational speed.
Proper citation: C-mii (RRID:SCR_010839) Copy
http://www.bioconductor.org/packages/devel/bioc/html/CGHnormaliter.html
Software for normalization and centralization of array comparative genomic hybridization (aCGH) data with imbalanced aberrations. The algorithm uses an iterative procedure that effectively eliminates the influence of imbalanced copy numbers. This leads to a more reliable assessment of copy number alterations (CNAs).
Proper citation: CGHnormaliter (RRID:SCR_002936) Copy
http://www.bioconductor.org/packages/release/bioc/html/chimera.html
A Bioconductor package that organizes, annotates, analyses and validates fusions reported by different fusion detection tools. The current implementation can deal with output from bellerophontes, chimeraScan, deFuse, fusionCatcher, FusionFinder, FusionHunter, FusionMap, mapSplice, Rsubread, tophat-fusion, tophat-fusion-post and STAR. The core of Chimera is a fusion data structure that can store fusion events detected with any of the aforementioned tools.
Proper citation: Chimera (RRID:SCR_002959) Copy
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