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https://code.google.com/p/peptide-shaker/

Software providing a search engine independent platform for visualization of peptide and protein identification results from multiple search engines, currently supporting X!Tandem, MS-GF+, MS Amanda, OMSSA, MyriMatch, Comet, Tide, Mascot and mzIdentML. By combining the results from multiple search engines, while re-calculating PTM localization scores and redoing the protein inference, PeptideShaker attempts to give you the best possible understanding of your proteomics data.

Proper citation: PeptideShaker (RRID:SCR_002520) Copy   

•   Source: SciCrunch Registry

http://www.opendoar.org/

A quality-controlled directory of academic open access repositories that provides a simple repository list, and lets you search for repositories or search repository contents. Additionally, tools and support to both repository administrators and service providers in sharing best practice and improving the quality of the repository infrastructure are provided. The current directory lists repositories and allows breakdown and selection by a variety of criteria which can also be viewed as statistical charts. The underlying database has been designed from the ground up to include in-depth information on each repository that can be used for search, analysis, or underpinning services like text-mining.

Proper citation: OpenDOAR (RRID:SCR_002641) Copy   

•   Source: SciCrunch Registry

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

Software algorithm that automatically estimates and removes physiological noise in BOLD fMRI data, including the effects of heartbeat and respiration. This algorithm (1) masks out high-variance CSF and vascular tracts that may otherwise confound analyses, and (2) regresses out noise timeseries in grey matter tissue, using an adaptive multivariate component decomposition (Canonical Autocorrelations Analysis). PHYCAA+ is an efficient, automated procedure that does NOT require external measures of physiology, nor does it require the user to manually identify noise components. Based on the peer-reviewed article: Churchill & Strother (2013). PHYCAA+: An Optimized, Adaptive Procedure for Measuring and Controlling Physiological Noise in BOLD fMRI. NeuroImage 82: 306-325

Proper citation: PHYCAA+: adaptive physiological noise correction for BOLD fMRI (RRID:SCR_002514) Copy   

•   Source: SciCrunch Registry

http://www.mementoweb.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. An extension for Chrome to see a version of a resource as it existed at some date in the past, by entering that URI in your browser and by specifying the desired date in a browser plug-in. Or you can actually browse the Web of the past by selecting a date and clicking. Whatever you land upon will be versions of Web resources as they were around the selected date. (This will only work if previous versions are available somewhere on the Web.)

Proper citation: Memento (RRID:SCR_002634) Copy   

•   Source: SciCrunch Registry

http://jcb-dataviewer.rupress.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A web-based, multi-dimensional image data-viewing application for original microscopy image datasets associated with articles published in The Journal of Cell Biology, a peer-reviewed journal published by The Rockefeller University Press. The JCB DataViewer can host multidimensional fluorescence microscopy images, 3D tomogram data, very large (gigapixel) images, and high content imaging screens. Images are presented in an interactive viewer, and the scores from high content screens are presented in interactive graphs with data points linked to the relevant images. The JCB DataViewer uses the Bio-Formats library to read over 120 different imaging file formats and convert them to the OME-TIFF image data standard. Image data are archived by the Journal and may be freely accessed by readers using the JCB DataViewer. Download of author-provided image data and associated metadata in OME-TIFF format is also possible with author permission, allowing for independent analysis of image data irrespective of acquisition or viewing software. Although the JCB DataViewer is designed to host and facilitate sharing and analysis of original microscopy image data, authors may also upload other types of original image data as supplements to their manuscripts, including histology and electron micrographs and digital scans of gels or blots.

Proper citation: JCB DataViewer (RRID:SCR_002633) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/pirs/

Software for de novo data simulation. It uses empirical distribution to reproduce Illumina pair-end reads with real distribution of substitution sequencing errors, quality values and GC%-depth bias.

Proper citation: pIRS (RRID:SCR_002519) Copy   

•   Source: SciCrunch Registry

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

A free software tool for Copy Number Variation (CNV) detection from SNP genotyping arrays. Currently it can handle signal intensity data from Illumina and Affymetrix arrays. With appropriate preparation of file format, it can also handle other types of SNP arrays and oligonucleotide arrays. PennCNV implements a hidden Markov model (HMM) that integrates multiple sources of information to infer CNV calls for individual genotyped samples. It differs form segmentation-based algorithm in that it considered SNP allelic ratio distribution as well as other factors, in addition to signal intensity alone. In addition, PennCNV can optionally utilize family information to generate family-based CNV calls by several different algorithms. Furthermore, PennCNV can generate CNV calls given a specific set of candidate CNV regions, through a validation-calling algorithm.

Proper citation: PennCNV (RRID:SCR_002518) Copy   

•   Source: SciCrunch Registry

https://pdbp.ninds.nih.gov

Common data management resource and web portal to promote discovery of Parkinson's Disease diagnostic and progression biomarker candidates for early detection and measurement of disease progression. PDBP will serve as multi-faceted platform for integrating existing biomarker efforts, standardizing data collection and management across these efforts, accelerating discovery of new biomarkers, and fostering and expanding collaborative opportunities for all stakeholders.

Proper citation: Parkinson’s Disease Biomarkers Program Data Management Resource (PDBP DMR) (RRID:SCR_002517) Copy   

•   Source: SciCrunch Registry

http://bioassayontology.org/

Ontology to describe and categorize chemical biology and drug screening assays and their results including high-throughput screening (HTS) data for the purpose of categorizing assays and data analysis. BAO is an extensible, knowledge-based, highly expressive (currently SHOIQ(D)) description of biological assays making use of descriptive logic based features of the Web Ontology Language (OWL). BAO currently has over 700 classes and also makes use of several other ontologies. It describes several concepts related to biological screening, including Perturbagen, Format, Meta Target, Design, Detection Technology, and Endpoint. Perturbagens are perturbing agents that are screened in an assay; they are mostly small molecules. Assay Meta Target describes what is known about the biological system and / or its components interrogated in the assay (and influenced by the Perturbagen). Meta target can be directly described as a molecular entity (e.g. a purified protein or a protein complex), or indirectly by a biological process or event (e.g. phosphorylation). Format describes the biological or chemical features common to each test condition in the assay and includes biochemical, cell-based, organism-based, and variations thereof. The assay Design describes the assay methodology and implementation of how the perturbation of the biological system is translated into a detectable signal. Detection Technology relates to the physical method and technical details to detect and record a signal. Endpoints are the final HTS results as they are usually published (such as IC50, percent inhibition, etc). BAO has been designed to accommodate multiplexed assays. All main BAO components include multiple levels of sub-categories and specification classes, which are linked via object property relationships forming an expressive knowledge-based representation.

Proper citation: Bioassay Ontology (RRID:SCR_002638) Copy   

•   Source: SciCrunch Registry

http://www.gudmap.org/Resources/Ontologies.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A high-resolution ontology has been developed by members of the GUDMAP consortium to describe the subcompartments of the developing murine genitourinary tract. This ontology incorporates what can be defined histologically and begins to encompass other structures and cell types already identified at the molecular level. The GUDMAP ontology encompasses Theiler stage (TS) 17-27 of development as well as the sexually mature adult. It has been written as a partonomic, text-based, hierarchical ontology that, for the embryological stages, has been developed as a high-resolution expansion of the existing Edinburgh Mouse Atlas Project (EMAP) ontology. It also includes group terms for well-characterized structural and/or functional units comprising several sub-structures, such as the nephron and juxtaglomerular complex. Each term has been assigned a unique identification number. Synonyms have been used to improve the success of query searching and maintain wherever possible existing EMAP terms relating to this organ system.

Proper citation: GUDMAP Ontology (RRID:SCR_002637) Copy   

•   Source: SciCrunch Registry

http://idealab.ucdavis.edu/software/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. A collection of software tools used for processing and organizing MRI data. The Dicom Importer allows you to to view, assemble, and organize dicom files. Subject Library is a filesystem-based search and reporting tool that can be configured to work with many different organization schemes. This package also contains a python library that can be used to write scripts for custom tasks.

Proper citation: Subject Library (RRID:SCR_002595) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/panda-tool/

Software matlab toolbox for pipeline processing of diffusion MRI images. For each subject, PANDA can provide outputs in 2 types: i) diffusion parameter data that is ready for statistical analysis; ii) brain anatomical networks constructed by using diffusion tractography. Particularly, there are 3 types of resultant diffusion parameter data: WM atlas-level, voxel-level and TBSS-level. The brain network generated by PANDA has various edge definitions, e.g. fiber number, length, or FA-weighted. The key advantages of PANDA are as follows: # fully-automatic processing from raw DICOM/NIFTI to final outputs; # Supporting both sequential and parallel computation. The parallel environment can be a single desktop with multiple-cores or a computing cluster with a SGE system; # A very friendly GUI (graphical user interface).

Proper citation: PANDA (RRID:SCR_002511) Copy   

•   Source: SciCrunch Registry

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

A set of command line tools allowing 2D and 3D image registration, mainly for medical imaging (although also relevant to other image registration problems).

Proper citation: TAPIR (RRID:SCR_002596) Copy   

•   Source: SciCrunch Registry

http://sve.bmap.ucla.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. An automated online framework for performing validation studies of skull-stripping methods. Registered users may download 40 T1 MRI volumes, skull-strip them with the algorithm of their choice, and upload their segmentation results to the SVE website. The server will then compare the 40 skull-stripped results against a set of manually generated brain masks. The server computes a series of measures for the uploaded data, including Jaccard and Dice measures. It also produces images for visualizing the spatial location of the segmentation errors relative to a common space. The results are archived on the server, and the measures are viewable by visitors to the site.

Proper citation: Segmentation Validation Engine (RRID:SCR_002591) Copy   

•   Source: SciCrunch Registry

http://www.dartmouth.edu/~nir/nirfast/

Software package for modeling Near-Infrared light transport in tissue and image reconstruction. This includes: Standard single wavelength absorption and reduced scatter, Multi-wavelength spectrally constrained models and Fluorescence models.

Proper citation: Nirfast (RRID:SCR_002503) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/plugins/mwiki/index.php/webmscaleapi:MainPage

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 13, 2026. Venue for discussing and defining standard web interfaces for sharing images, annotations, and analyses of multiscale biological images. The goal is to increase interoperability of code to share the burden of infrastructure, increase code reuse, and allow us to spend more time focused on scientific questions. Please visit our Wiki to start participating. Together we can develop a small group of interfaces which are easy to implement, extensible, and cover the major tasks of developing tools for multiscale data on the web.

Proper citation: Web Interfaces for Multiscale Images (RRID:SCR_002589) Copy   

•   Source: SciCrunch Registry

http://ckan.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. A complete out-of-the-box data management software solution that makes data accessible by providing tools to streamline publishing, sharing, finding and using data. CKAN is aimed at data publishers (national and regional governments, companies and organizations) wanting to make their data open and available. It uses its internal model to store metadata about the different records, and presents it on a web interface that allows users to browse and search this metadata. It also offers a powerful API that allows third-party applications and services to be built around it. CKAN is built with Python on the backend and Javascript on the frontend, and uses the Pylons web framework and SQLAlchemy as its ORM. Its database engine is PostgreSQL and its search is powered by SOLR. It has a modular architecture that allows extensions to be developed to provide additional features such as harvesting or data upload. CKAN is currently used by governments and user groups worldwide to power both official and community data portals.

Proper citation: CKAN (RRID:SCR_002622) Copy   

•   Source: SciCrunch Registry

http://www.osmicenterprises.com

A computerized, odor delivery device that can be used for basic research applications including mapping olfactory centers, cognitive / learning research, neuro-marketing among other uses. Additional products including tests for odor threshold, odor identification, odor discrimination and odor memory.

Proper citation: OEI: fMRI compatible olfactometer (RRID:SCR_002507) Copy   

•   Source: SciCrunch Registry

http://www.nirep.org/

Project to develop software tools and provide shared image validation databases for rigorous testing of non-rigid image registration algorithms. NIREP will extend the scope of prior validation projects by developing evaluation criteria and metrics using large image populations, using richly annotated image databases, using computer simulated data, and increasing the number and types of evaluation criteria. The goal of this project is to establish, maintain, and endorse a standardized set of relevant benchmarks and metrics for performance evaluation of nonrigid image registration algorithms. Furthermore, these standards will be incorporated into an exportable computer program to automatically evaluate the registration accuracy of nonrigid image registration algorithms.

Proper citation: Non-Rigid Image Registration Evaluation Project (RRID:SCR_002505) Copy   

•   Source: SciCrunch Registry

http://biodbcore.org

A community-defined, uniform, generic description of the core attributes of biological databases. The BioDBCore checklist is overseen by the International Society for Biocuration (ISB), in collaboration with the BioSharing forum. A catalogue of databases, described according to the BioDBcore guidelines, along with the standards used within them have been partly compiled with the support of Oxford University Press and Re3Data.org. Database providers are encouraged to either create or claim their BioDBCore entry and update it as appropriate., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: bioDBcore (RRID:SCR_002781) Copy   

•   Source: SciCrunch Registry