Tools   Select Another Resource Report Type

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

Tool to assist site staff with curation of data dictionary, data item, and subject item files for preparation to uploading and sharing data with DbGaP resource.

Proper citation: DbGaP Cleaner (RRID:SCR_009462) Copy   

•   Source: SciCrunch Registry

http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) Copy   

•   Source: SciCrunch Registry

http://www.rogue-research.com

Neuronavigation system for use in human cognitive neuroscience (TMS, EEG, NIRS) and for non-human neurosurgical applications.

Proper citation: Brainsight (RRID:SCR_009539) Copy   

•   Source: SciCrunch Registry

http://www.imagilys.com/brainmagix-spm-viewer/

A free, professional viewer for SPM fMRI results. SPM (Statistical Parametric Mapping, UCL, London) is a powerful fMRI analysis software but its visualization capabilities are sometimes a limitation for the researchers. That's why Imagilys has decided to offer the neuroimaging community a free version of its commercial "BrainMagix" neuroimaging software, called "BrainMagix SPM viewer". BrainMagix SPM Viewer's Features - Professional viewer for your SPM-based fMRI activations - JAVA-programmed, cross-platform (Windows, MAC, Linux), without Matlab license, making it possible to share your results with colleagues who do not have SPM installed - Reads SPM.mat files and NIfTI images in an user-friendly way - Overlay the blobs with an atlas or any anatomical image - On the fly adjustment of threshold and cluster size - Localize your activations in an atlas - BOLD signal curves in ROIs (future feature) - Export your results as PNG images

Proper citation: BrainMagix SPM Viewer (RRID:SCR_009537) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/brains-inner-workings/the-brains-inner-workings-activities-for-grades-9-through-12.shtml

This comprehensive free collection of multimedia resources and inquiry-based activities tied to the National Science Education Standards help teachers and students learn about the structure, function and cognitive aspects of the human brain. The packet includes a teacher's manual, student manual, DVD of videos, and a CDROM of accompanying materials.

Proper citation: Brain's Inner Workings: Activities for Grades 9 through 12 (RRID:SCR_008842) Copy   

•   Source: SciCrunch Registry

http://en.wikibooks.org/wiki/Pharmacology

Pharmacology is a wikibook covering topics within pharmacology and pharmaceutical sciences.

Proper citation: Pharmacology (RRID:SCR_009017) Copy   

•   Source: SciCrunch Registry

http://web1.sph.emory.edu/bios/CBIS/download_page.php

A statistical and graphical visualization MATLAB toolbox for the analysis of fMRI data, called the Bayesian Spatial Model for activation and connectivity (BSMac). BSMac simultaneously performs whole-brain activation analyses at the voxel and region of interest levels as well as task-related functional connectivity (FC) analyses using a flexible Bayesian modeling framework (Bowman et al., 2008). BSMac allows for inputting data in either Analyze or Nifti file formats. The user provides information pertaining to subgroup memberships, scanning sessions, and experimental tasks (stimuli), from which the design matrix is constructed. BSMac then performs parameter estimation based on MCMC methods and generates plots for activation and FC, such as interactive 2D maps of voxel and region-level task-related changes in neural activity and animated 3D graphics of the FC results.

Proper citation: BSMac (RRID:SCR_009531) Copy   

•   Source: SciCrunch Registry

http://www.readout.info

Matlab toolbox that makes it easy to apply decoding analyses to neural data. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and examples are given on how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations.

Proper citation: Neural Decoding Toolbox (RRID:SCR_009012) Copy   

•   Source: SciCrunch Registry

http://pages.stat.wisc.edu/~yandell/qtl/software/qtlbim/

Software library for QTL Bayesian Interval Mapping that provides a Bayesian model selection approach to map multiple interacting QTL. It works on experimentally inbred lines and performs a genome-wide search to locate multiple potential QTL. The package can handle continuous, binary and ordinal traits. (entry from Genetic Analysis Software)

Proper citation: R/QTLBIM (RRID:SCR_009375) Copy   

•   Source: SciCrunch Registry

http://www.cori.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 5, 2022. Endoscopic Reporting Software, aggregated and individual research data and tailor-made services aimed to advance the overall practice of endoscopy. It was developed to study outcomes of gastrointestinal (GI) endoscopic procedures in real life settings, using data obtained from the CORI Endoscopic Reporting Software or from other endoscopic reporting software. Practice sites include hospitals, ambulatory care centers, private practices, universities, and Veteran''''s hospitals (VA''''s). The CORI v4 Endoscopic Reporting Software is a specialty Electronic Health Record used to document endoscopic procedures and provide reporting services to your practice. Data from participating providers is also sent to a central data repository to become part of the National Endoscopic Database (NED), which now contains data from over 2.7 million GI procedures. The CORI v4 Endoscopic Reporting Software offers significant benefits for participating practices, providers and patients, as well as for everyone who benefits from CORI''''s research efforts. You may actively participate in research with CORI. If you have ideas for research using the NED, their research team can help you evaluate those ideas, collect and analyze the data. In addition, you may choose to participate in one of the prospective research projects conducted by CORI research staff.

Proper citation: Clinical Outcomes Research Initiative (RRID:SCR_009010) Copy   

•   Source: SciCrunch Registry

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

Suite of tools for brain image analysis. Image manipulation, 2D visualization, linear alignment, BBSI, template-based bias correction, skullstrip. GUI Image analysis tools. Now modified to read/write single file nifti (.nii) format. Other packages to be added.

Proper citation: IDeA Lab brain image processing suite (RRID:SCR_009495) Copy   

•   Source: SciCrunch Registry

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

A method for group-wise image registration by pairwisely registering similar images identified using graph theoretic techniques. Particularly, they use sparse coding to estimate image similarity measures among images to be registered, yielding asymmetric, group-wise image similarity measures for each image to others in the group.

Proper citation: Groupwise Image Registration Toolbox (RRID:SCR_009492) Copy   

•   Source: SciCrunch Registry

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

An international effort to establish resources necessary to study the application of neuroimaging measures as (surrogate) biomarkers in Huntington''s Disease (HD). The primary aims are to develop and apply software tools, imaging protocols, quality control procedures, data archiving, data distribution, and participation guidelines that will accelerate existing and prospective imaging studies.

Proper citation: HD Neuro-Informatics (RRID:SCR_009493) Copy   

•   Source: SciCrunch Registry

https://github.com/BRAINSia/BRAINSTools/tree/master/BRAINSMush

Tool to generate brain volume mask from input of T1 and T2-weighted images alongside a region of interest brain mask. This volume mask omits dura, skull, eyes, etc. The program is built upon ITK and uses the Slicer3 execution model framework to define the command line arguments and can be fully integrated with Slicer3 using the module discovery capabilities of Slicer3.

Proper citation: BRAINSMush (RRID:SCR_009485) Copy   

•   Source: SciCrunch Registry

http://meme.nbcr.net/meme/cgi-bin/gomo.cgi

Gene Ontology for Motifs (GOMO) is an alignment- and threshold-free comparative genomics approach for assigning functional roles to DNA regulatory motifs from DNA sequence. The algorithm detects associations between a user-specified DNA regulatory motif (expressed as a position weight matrix; PWM) and Gene Ontology terms. The original method for predicting the roles of transcription factors (TFs starts with a PWM motif describing the DNA-binding affinity of the TF. GOMO uses the PWM to score the promoter region of each gene in the genome for its likelihood to be bound by the TF. The resulting ''''affinity'''' scores are then used to test each term in the Gene Ontology for association with high-scoring genes. The algorithm was subsequently extended to leverage conserved signals using multiple, related species in a comparative approach, which greatly improves the resulting annotations. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOMO - Gene Ontology for Motifs (RRID:SCR_008864) Copy   

•   Source: SciCrunch Registry

http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=renal

An integrated resource for information on genes, QTLs and strains associated with a variety of kidney and renal system conditions such as Renal Hypertension, Polycystic Kidney Disease and Renal Insufficiency, as well as Kidney Neoplasms.

Proper citation: Renal Disease Portal (RRID:SCR_009030) Copy   

•   Source: SciCrunch Registry

http://www.ngdc.noaa.gov/

National Data Center that provides scientific stewardship, products, and services for geophysical data from sea floor and solid earth environments, including Earth observations from space. Please note that routine underway geophyiscal shipboard data collected with standard equipment aboard the UNOLS fleet (e.g. bathymetry, subbottom, magnetics, gravity) are routinely transmitted to NGDC via Rolling Deck to Repository (R2R).

Proper citation: National Geophysical Data Center (RRID:SCR_009429) Copy   

•   Source: SciCrunch Registry

https://www.ncdc.noaa.gov/

National Data Center that accepts and makes available weather, climate, paleoclimate, meteorological data.

Proper citation: National Climatic Data Center (RRID:SCR_009427) Copy   

•   Source: SciCrunch Registry

http://cocomac.org/WWW/paxinos3D/index.html

An interactive interface of macaque stereotaxic atlas with a connectivity database, allowing integrated data analysis and mapping between 3D structures with database vocabularies. These Java-based tools are capable of reading stacks of polygons described in svg vector format and arrange them in 3D space so that the corresponding structures can be viewed and manipulated individually. An additional excel (currently v. 1997-2003) file maintains the structure abbreviations and their mapping to the terminology of databases that provide supplementary information. Here in particular we have manually drawn the cortical, striatal, thalamic and amygdaloid structures of the 151 frontal sections from the Rhesus Monkey Brain in Stereotactic Coordinates authored by Paxinos and colleagues in 1999. After loading the excel file and a set of the svg files, the view can be rotated, zoomed and individual brain structures be selected for identification and simple geometric measures. A stereotaxic grid is a display option. The abbreviations of the brain structures are mapped to entities recorded in the CoCoMac database of primate brain connectivity. Thereby one can retrieve mapping and connectivity information for the selected structure as text or connecting arrows.

Proper citation: CoCoMac-Paxinos3D viewer (RRID:SCR_009548) Copy   

•   Source: SciCrunch Registry

https://portal.dbmi.hms.harvard.edu/projects/GRDR/

Data repository of de-identified patient data, aggregated in a standardized manner, to enable analyses across many rare diseases and to facilitate various research projects, clinical studies, and clinical trials. The aim is to facilitate drug and therapeutics development, and to improve the quality of life for the many millions of people who are suffering from rare diseases. The goal of GRDR is to enable analyses of data across many rare diseases and to facilitate clinical trials and other studies. During the two-year pilot program, a web-based template will be developed to allow any patient organization to establish a rare disease patient registry. At the conclusion of the program, guidance will be available to patient groups to establish a registry and to contribute de-identified patient data to the GRDR repository. A Request for Information (RFI) was released on February 10, 2012 requesting information from patient groups about their interest in participating in a GRDR pilot project. ORDR selected 30 patient organizations to participate in this pilot program to test the different functionalities of the GRDR. Fifteen (15) organizations with established registries and 15 organizations that do not have patient registry. The 15 patient groups, each without a registry, were selected to assist in testing the implementation of the ORDR Common Data Elements (CDEs) in the newly developed registry infrastructure. These organizations will participate in the development and promotion of a new patient registry for their rare disease. The GRDR program will fund the development and hosting of the registry during the pilot program. Thereafter, the patient registry is expected to be self-sustaining.The 15 established patient registries were selected to integrate their de-identified data into the GRDR to evaluate the data mapping and data import/export processes. The GRDR team will assist these organizations in mapping their existing registry data to the CDEs. Participating registries must have a means to export their de-identified registry data into a specified data format that will facilitate loading the data into the GRDR repository on a regular basis. The GRDR will also develop the capability to link patients'''' data and medical information to donated biospecimens by using a Voluntary Global Unique Patient Identifier (GUID). The identifier will enable the creation of an interface between the patient registries that are linked to biorepositories and the Rare Disease Human Biospecimens/Biorepositories (RD-HUB) http://biospecimens.ordr.info.nih.gov/.

Proper citation: GRDR (RRID:SCR_008978) Copy   

•   Source: SciCrunch Registry