Tools   Select Another Resource Report Type

http://cancergenome.nih.gov/

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

Proper citation: The Cancer Genome Atlas (RRID:SCR_003193) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/igblast/

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on January 4,2023. IgBLAST was developed at NCBI to facilitate analysis of immunoglobulin V region sequences in GenBank. In addition to performing a regular BLAST search, IgBLAST has several additional functions: - Reports the germline V, D and J gene matches to the query sequence. - Annotates the immunoglobulin domains (FWR1 through FWR3). - Matches the returned hits (for databases other than germline genes) to the closest germline V genes, making it easier to identify related sequences. - Reveals the V(D)J junction details such as nucleotide homology between the ends of V(D)J segments and N nucleotide insertions. D and J gene reporting is only for nucleotide sequence search and requires a stretch of five or more nucleotide identity between the query and D or J genes. Sponsors: This resource is supported by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine.

Proper citation: IgBLAST (RRID:SCR_002873) Copy   

•   Source: SciCrunch Registry

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

Anatomical atlases constructed by Computational Anatomy of Johns Hopkins University for analysis of shape vectors. The atlases were generated from segmented hippocampal and amygdala structures in acquired populations of children, adolescents and young adults in neuroimaging studies of major depression disorder (MDD) at Washington University at St Louis.

Proper citation: Atlases of amygdala and hippocampus for pediatric populations (RRID:SCR_014085) Copy   

•   Source: SciCrunch Registry

https://github.com/stamatak/ExaML

Source code for large-scale phylogenetic analyses on whole-transcriptome and whole-genome alignments using supercomputers.

Proper citation: Examl (RRID:SCR_016087) Copy   

•   Source: SciCrunch Registry

http://mzmatch.sourceforge.net/

A software to provide small tools for common processing tasks for LC/MS data. It is an extension to the metabolomics analysis pipeline mzMatch.R. The software is modular, open source, platform independent and written in Java.

Proper citation: mzMatch (RRID:SCR_000543) Copy   

•   Source: SciCrunch Registry

http://www.synaptosoft.com/MiniAnalysis/

Software tool that detects peaks of any type, any shape, any direction, and any size for neuroscientists who are studying spontaneous activities. Allows detection of virtually any kind of peaks including spontaneous miniature synaptic currents and potentials, action potential spikes, calcium imaging peaks, amperometric peaks, ECG peaks etc. It includes the complex and multiple peak detection algorithm. Has post-detection analyses including essential plots and statistical parameters. Group Analysis provides specialized and detailed analysis options for action potentials, decay fitting, fEPSP/population spikes, amperometry, etc., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Mini Analysis Program (RRID:SCR_002184) Copy   

•   Source: SciCrunch Registry

http://cmb.gis.a-star.edu.sg/ChIPSeq/paperChIPSeq.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 12, 2017. A software tool to find peaks from ChIPSeq data generated from the Solexa/Illumina platform., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ChIPSeq Peak Finder (RRID:SCR_002081) Copy   

•   Source: SciCrunch Registry

http://brainproducts.com/productdetails.php?id=17

Software to manage the daily work of analyzing various neurophysiological data. Features include a history tree, automated analysis, various data format readers, and more.

Proper citation: BrainVision Analyzer (RRID:SCR_002356) Copy   

•   Source: SciCrunch Registry

http://camera.calit2.net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016; however, the URL provides links to associated projects and data. A suite of data query, download, upload, analysis and sharing tools serving the needs of the microbial ecology research community, and other scientists using metagenomics data.

Proper citation: Community Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis (RRID:SCR_002676) Copy   

•   Source: SciCrunch Registry

http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

•   Source: SciCrunch Registry

http://neuromorphometrics.org:8080/nvm/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 6, 2023. Software tool for quantitative neuroanatomical measurements in volumetric image data. Used to draw regions of interest for subsequent fMRI analysis.

Proper citation: NVM (RRID:SCR_000600) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/university-of-colorado-at-boulder

A portal for the core labs and facilities at the University of Colorado at Boulder.

Proper citation: University of Colorado at Boulder Labs and Facilities (RRID:SCR_001054) Copy   

•   Source: SciCrunch Registry

http://www.ezbioresearch.com

A biotechnology company that develops, manufactures and distributes molecular biology tool kits and laboratory consumable products. Services include DNA and RNA microarrays, PCR and transgenic genotyping, and DNA/RNA analysis and quality control.

Proper citation: EZ BioResearch (RRID:SCR_001050) Copy   

•   Source: SciCrunch Registry

https://www.cmtk.org/

A Python-based open source toolkit for magnetic resonance connectome mapping, data management, sharing, visualization and analysis. The toolkit includes the connectome mapper (a full DMRI processing pipeline), a new file format for multi modal data and metadata, and a visualization application.

Proper citation: Connectome Mapping Toolkit (RRID:SCR_001644) Copy   

•   Source: SciCrunch Registry

http://dti-tk.sourceforge.net/pmwiki/pmwiki.php

A spatial normalization and atlas construction toolkit optimized for examining white matter morphometry using DTI data with special care taken to respect the tensorial nature of the data. It implements a state-of-the-art registration algorithm that drives the alignment of white matter (WM) tracts by matching the orientation of the underlying fiber bundle at each voxel. The algorithm has been shown to both improve WM tract alignment and to enhance the power of statistical inference in clinical settings. A 2011 study published in NeuroImage ranks DTI-TK the top-performing tool in its class. Key features include: * open standard-based file IO support: NIfTI format for scalar, vector and tensor image volumes * tool chains for manipulating tensor image volumes: resampling, smoothing, warping, registration & visualization * pipelines for WM morphometry: spatial normalization & atlas construction for population-based studies * built-in cluster-computing support: support for open source Sun Grid Engine (SGE) * Interoperability with other popular DTI tools: AFNI, Camino, FSL & DTIStudio * Interoperability with ITK-SNAP: support multi-modal visualization and segmentation

Proper citation: Diffusion Tensor Imaging ToolKit (RRID:SCR_001642) Copy   

•   Source: SciCrunch Registry

http://tbi.ci.uchicago.edu/

Project to define a roadmap for diffusion MR imaging of traumatic brain imaging and design an infrastructure to implement the recommendations and tested to ensure feasibility, disseminate results, and facilitate deployment and adoption. The research roadmap and infrastructure development will concentrate on three areas: 1) standardization of diffusion imaging methodology, 2) trial design and patient selection for acute or chronic therapy, and 3) development of multi-center collaborations and repositories for evaluating whether advanced diffusion imaging does improve decision making and TBI patients' outcomes. # DTI MRI reproducability: One of the major areas of investigation in this project is to study the reproducibility of data acquisition and image analysis algorithms. Understanding reproducibility defines a base level of deviation from which scans can be analyzed with statistical significance. As part of this work they are also developing site qualification criteria with the intention of setting limits on the MR system minimal performance for acceptable use in TBI evaluation. # Infrastructure for image storage, analysis and visualization: There is a continuing need to refine and extend software methods for diffusion MRI data analysis and visualization. Not only to translate tools into clinical practice, but also to encourage continuation of the innovation and development of new tools and techniques. To deliver upon these goals they are designing and implementing a storage and computational infrastructure to provide access to shared datasets and intuitive interfaces for analysis and visualization through a variety of tools. A strong emphasis has been placed on providing secure data sharing and the ability to add community defined common data elements. The infrastructure is built upon a Software-as-a-Service model, in which tools are hosted and managed remotely allowing users access through well-defined interfaces. The final service will also facilitate composition or orchestration of workflows composed of different analysis and processing tasks (for example using LONI or XNAT pipelines) with the ultimate goal of providing automated no-click evaluations of diffusion MRI data. # Tool development: The final aspect of this project aims to facilitate and encourage tool development and contribution. By providing access to open datasets, they will create a platform on which tool developers can compare and improve and their tools. When tools are sufficiently mature they can be exposed in the infrastructure mentioned above and used by researchers and other developers.

Proper citation: Diffusion MRI of Traumatic Brain Injury (RRID:SCR_001637) Copy   

•   Source: SciCrunch Registry

http://neuroimage.usc.edu/brainstorm/

Software as collaborative, open source application dedicated to analysis of brain recordings: MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. User-Friendly Application for MEG/EEG Analysis.

Proper citation: Brainstorm (RRID:SCR_001761) Copy   

•   Source: SciCrunch Registry

http://www.licor.com/bio/products/software/image_studio_lite/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 28,2023. Software application which can analyze basic Western blot data and export them for use in spreadsheet programs. Users can create standardized or custom lab reports and can share them with colleagues. Image Studio Lite has been discontinued and replaced with Empiria Studio Software.

Proper citation: Image Studio Lite (RRID:SCR_013715) Copy   

•   Source: SciCrunch Registry

https://skyline.gs.washington.edu/labkey/project/home/software/Skyline/begin.view

Software tool as Windows client application for targeted proteomics method creation and quantitative data analysis. Open source document editor for creating and analyzing targeted proteomics experiments. Used for large scale quantitative mass spectrometry studies in life sciences.

Proper citation: Skyline (RRID:SCR_014080) Copy   

•   Source: SciCrunch Registry

http://www.originlab.com/index.aspx?go=PRODUCTS/Origin

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 4, 2025.Software application for data analysis and graphing. Origin contains a variety of different graph types, including statistical plots, 2D and 3D vector graphs, and counter graphs. More advance version is OriginPro which offers advanced analysis tools and Apps for Peak Fitting, Surface Fitting, Statistics and Signal Processing.

Proper citation: Origin (RRID:SCR_014212) Copy   

•   Source: SciCrunch Registry