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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

https://www.drugabuse.gov/publications/drugfacts/genetics-epigenetics-addiction

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. An archived video on the web providing comprehensive and hands-on training in genetics and epigenetic methodology. The purpose of the course is to provide an introduction to approaches and tools for identifying genes that confer vulnerability to addiction and individual differences in responses to treatments. The course is targeted to those who are new to the field of addiction genetics. The course was held over 5 days with lectures and hands-on demonstrations given each day. Viewers of the course will gain familiarity with conceptual and practical approaches to complex disorders using relevant genetic and epigenetic databases, and appropriate statistical and empirical approaches. Topics covered Behavioral genetics, genetic epidemiology, twin and adoption studies, statistical genetic concepts and approaches for mapping complex traits, haplotype based approaches for association mapping, genome-wide scans for addictive disorders, application of linkage for mapping genes and genetic loci for addictive disorders, pharmacogenomics of treatment of addictive disorders, Baysian Methods for identifying gene-gene interactions, analysis of copy number variation, practical use of genetic databases, mapping of complex traits in mice, methods for analyzing gene expression, and methods for doing epigenetic analysis are covered. The course was held April 4, 2008, at the Bethesda North Marriott Hotel and Conference Center, 5701 Marinelli Road, Bethesda, MD 20852.

Proper citation: Short Course on the Genetics and Epigenetics of Addiction National Institute on Drug Abuse: Archived Video (RRID:SCR_002783) Copy   

•   Source: SciCrunch Registry

http://genespeed.ccf.org/home/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. Database and customized tools to study the PFAM protein domain content of the transcriptome for all expressed genes of Homo sapiens, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans tethered to both a genomics array repository database and a range of external information resources. GeneSpeed has merged information from several existing data sets including the Gene Ontology Consortium, InterPro, Pfam, Unigene, as well as micro-array datasets. GeneSpeed is a database of PFAM domain homology contained within Unigene. Because Unigene is a non-redundant dbEST database, this provides a wide encompassing overview of the domain content of the expressed transcriptome. We have structured the GeneSpeed Database to include a rich toolset allowing the investigator to study all domain homology, no matter how remote. As a result, homology cutoff score decisions are determined by the scientist, not by a computer algorithm. This quality is one of the novel defining features of the GeneSpeed database giving the user complete control of database content. In addition to a domain content toolset, GeneSpeed provides an assortment of links to external databases, a unique and manually curated Transcription Factor Classification list, as well as links to our newly evolving GeneSpeed BetaCell Database. GeneSpeed BetaCell is a micro-array depository combined with custom array analysis tools created with an emphasis around the meta analysis of developmental time series micro-array datasets and their significance in pancreatic beta cells.

Proper citation: GeneSpeed- A Database of Unigene Domain Organization (RRID:SCR_002779) Copy   

•   Source: SciCrunch Registry

http://liulab.dfci.harvard.edu/BINOCh/

Software that infers the identity of transcription factors used to regulate cell response to stimulus or determine a program of differentiation. It uses genome wide information on enhancer proximal nucleosome occupancy, acquired using ChIP-seq targeting enhancer related histone modifications., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: BINOCh (RRID:SCR_002778) Copy   

•   Source: SciCrunch Registry

http://www.nikoninstruments.com/Products/Software/NIS-Elements-Basic-Research

Software tool for acquisition and device control for standard research applications, requiring four dimensional imaging. Provides access to advanced image capture, archiving, and analysis solutions that are easy-to-use and provide maximum workflow. Handles multi dimensional imaging with support for capture, display, data management, analysis and additional options for peripheral device control, and multi-dimensional acquisition. Provides advanced image processing options such as database capabilities and report generation, intensity over time measurement, and Extended Depth of Focus functionality.

Proper citation: NIS-Elements Basic Research (RRID:SCR_002776) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/RAD

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on March 24, 2014. A resource for gene expression studies, storing highly curated MIAME-compliant studies (i.e. experiments) employing a variety of technologies such as filter arrays, 2-channel microarrays, Affymetrix chips, SAGE, MPSS and RT-PCR. Data were available for querying and downloading based on the MGED ontology, publications or genes. Both public and private studies (the latter viewable only by users having appropriate logins and permissions) were available from this website. Specific details on protocols, biomaterials, study designs, etc., are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format. RAD is part of a more general Genomics Unified Schema (http://gusdb.org), which includes a richly annotated gene index (http://allgenes.org), thus providing a platform that integrates genomic and transcriptomic data from multiple organisms. NOTE: Due to changes in technology and funding, the RAD website is no longer available. RAD as a schema is still very much active and incorporated in the GUS (Genomics Unified Schema) database system used by CBIL (EuPathDB, Beta Cell Genomics) and others. The schema for RAD can be viewed along with the other GUS namespaces through our Schema Browser.

Proper citation: RNA Abundance Database (RRID:SCR_002771) Copy   

•   Source: SciCrunch Registry

http://learn.genetics.utah.edu/content/addiction/

A physiologic and molecular look at drug addiction involving many factors including: basic neurobiology, a scientific examination of drug action in the brain, the role of genetics in addiction, and ethical considerations. Designed to be used by students, teachers and members of the public, the materials meet selected US education standards for science and health. Drug addiction is a chronic disease characterized by changes in the brain which result in a compulsive desire to use a drug. A combination of many factors including genetics, environment and behavior influence a person's addiction risk, making it an incredibly complicated disease. The new science of addiction considers all of these factors - from biology to family - to unravel the complexities of the addicted brain. * Natural Reward Pathways Exist in the Brain: The reward pathway is responsible for driving our feelings of motivation, reward and behavior. * Drugs Alter the Brain's Reward Pathway: Drugs work over time to change the reward pathway and affect the entire brain, resulting in addiction. * Genetics Is An Important Factor In Addiction: Genetic susceptibility to addiction is the result of the interaction of many genes. * Timing and Circumstances Influence Addiction: If you use drugs when you are an adolescent, you are more likely to develop lifetime addiction. An individual's social environment also influences addiction risk. * Challenges and Issues in Addiction: Addiction impacts society with many ethical, legal and social issues.

Proper citation: New Science of Addiction: Genetics and the Brain (RRID:SCR_002770) Copy   

•   Source: SciCrunch Registry

http://www.genedb.org/Homepage

Database of genomes at various stages of completion, from early access to partial genomes with automatic annotation through to complete genomes with extensive manual curation. Its primary goals are: 1) to provide reliable access to the latest sequence data and annotation/curation for the whole range of organisms sequenced by the Pathogen group, and 2) to develop the website and other tools to aid the community in accessing and obtaining the maximum value from these data.

Proper citation: GeneDB (RRID:SCR_002774) Copy   

•   Source: SciCrunch Registry