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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   

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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   

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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   

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http://www.cognitiveatlas.org/

Knowledge base (or ontology) that characterizes the state of current thought in cognitive science that captures knowledge from users with expertise in psychology, cognitive science, and neuroscience. There are two basic kinds of knowledge in the knowledge base. Terms provide definitions and properties for individual concepts and tasks. Assertions describe relations between terms in the same way that a sentence describes relations between parts of speech. The goal is to develop a knowledge base that will support annotation of data in databases, as well as supporting improved discourse in the community. It is open to all interested researchers. A fundamental feature of the knowledge base is the desire and ability to capture not just agreement but also disagreement regarding definitions and assertions. Thus, if you see a definition or assertion that you disagree with, then you can assert and describe your disagreement. The project is led by Russell Poldrack, Professor of Psychology and Neurobiology at the University of Texas at Austin in collaboration with the UCLA Center for Computational Biology (A. Toga, PI) and UCLA Consortium for Neuropsychiatric Phenomics (R. Bilder, PI). Most tasks used in cognitive psychology research are not identical across different laboratories or even within the same laboratory over time. A major advantage of anchoring cognitive ontologies to the measurement level is that the strategy for determining changes in task properties is easier than tracking changes in concept definitions and usage. The process is easier because task parameters are usually (if not always) operationalized objectively, offering a clear basis to judge divergence in methods. The process is also easier because most tasks are based on prior tasks, and thus can more readily be considered descendants in a phylogenetic sense.

Proper citation: Cognitive Atlas (RRID:SCR_002793) Copy   

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http://berkeleybop.org/pkb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This interface is for exploring data collected as part of the NIF Neurodegenerative Disease Ontology project. Not generally intended for public consumption yet, but people are welcome to look - large caveat emptor applies. Sponsors: This resource is part of the NIF project.

Proper citation: OBD-PKB Interface (RRID:SCR_002882) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/biocaster-ontology/

A multilingual application ontology aimed at the early detection of public health events in the media. It aims to describe the terms and relations necessary to detect and risk assess public health events in the grey literature at an early stage; and bridge the gap between the (multilingual) grey literature and existing standards in biomedicine. The BCO focuses on the usage of terms and relations within informal unstructured reports which are often made at a pre-diagnostic stage of a disease outbreak by non-medically trained reporters. This is done to provide monitoring and early warning about public health hazards from online media reports.

Proper citation: BioCaster Ontology (RRID:SCR_003122) Copy   

•   Source: SciCrunch Registry

http://briansimulator.org/

Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.

Proper citation: Brian Simulator (RRID:SCR_002998) Copy   

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http://purl.bioontology.org/ontology/LIPRO

An ontology that describes the LIPIDMAPS nomenclature classification explicitly using description logics (OWL-DL). Lipid classes are organized hierarchically with the super-classes restricted by generic necessary conditions. More specific necessary conditions are used to define membership requirements for sub classes of lipid according to appropriate functional groups. Lipid research is increasingly integrated within systems level biology such as lipidomics where lipid classification is required before appropriate annotation of chemical functions can be applied.

Proper citation: Lipid Ontology (RRID:SCR_003349) Copy   

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http://purl.bioontology.org/ontology/APO

A structured controlled vocabulary for the phenotypes of Ascomycete fungi.

Proper citation: Ascomycete Phenotype Ontology (RRID:SCR_003254) Copy   

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http://purl.bioontology.org/ontology/MMO

An ontology designed to represent the variety of methods used to make qualitative and quantitative clinical and phenotype measurements both in the clinic and with model organisms.

Proper citation: Measurement Method Ontology (RRID:SCR_003373) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/bcgo-ontology/

An application ontology built for the Beta Cell Genomics database aiming to support database annotation, complicated semantic queries, and automated cell type classification. The ontology is developed using Basic Formal Ontology (BFO) as upper ontology, Ontology for Biomedical Investigations (OBI) as ontology framework and integrated subsets of multiple OBO Foundry (candidate) ontologies. Current the BCGO contains 2383 classes including terms referencing to 24 various OBO Foundry ontologies including CL, CLO, UBERON, GO, PRO, UO, etc.

Proper citation: Beta Cell Genomics Ontology (RRID:SCR_003259) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IDOMAL

An application ontology to cover all aspects of malaria (clinical, epidemiological, biological, etc) as well as the intervention attempts to control it, extending the infectious disease ontology (IDO).

Proper citation: Malaria Ontology (RRID:SCR_003369) Copy   

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http://purl.bioontology.org/ontology/MAT

An ontology of minimal set of terms for anatomy.

Proper citation: Minimal Anatomical Terminology (RRID:SCR_003385) Copy   

•   Source: SciCrunch Registry

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

Ontology developed as an application ontology as part of the Biocode Commons project whose goal is to support the interoperability of biodiversity data, including data on museum collections, environmental and metagenomic samples, and ecological surveys. It includes consideration of the distinctions between individuals, organisms, voucher specimens, lots, and samples the relations between these entities, and processes governing the creation and use of samples. Within scope as well are properties including collector, location, time, storage environment, containers, institution, and collection identifiers.

Proper citation: Biological Collections Ontology (RRID:SCR_003262) Copy   

•   Source: SciCrunch Registry

http://www.bioontology.org/wiki/index.php/CARO:Main_Page

An ontology developed to facilitate interoperability between existing anatomy ontologies for different species, and to provide a template for building new anatomy ontologies.

Proper citation: Common Anatomy Reference Ontology (RRID:SCR_003296) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CMO

An ontology designed to be used to standardize morphological and physiological measurement records generated from clinical and model organism research and health programs.

Proper citation: Clinical Measurement Ontology (RRID:SCR_003291) Copy   

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https://github.com/rsc-ontologies/rsc-cmo

An ontology that describes methods used to collect data in chemical experiments, such as mass spectrometry and electron microscopy; preparing and separating material for further analysis, such as sample ionization, chromatography, and electrophoresis; and synthesizing materials, such as epitaxy and continuous vapor deposition. It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns. It is intended to be complementary to the Ontology for Biomedical Investigations (OBI).

Proper citation: Chemical Methods Ontology (RRID:SCR_003286) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FYPO

A formal ontology of phenotypes observed in fission yeast that is being developed to support the comprehensive and detailed representation of phenotypes in PomBase, the online fission yeast resource. Its scope is similar to that of the Ascomycete Phenotype Ontology (APO), but FYPO includes more detailed pre-composed terms as well as computable definitions.

Proper citation: Fission Yeast Phenotype Ontology (RRID:SCR_003315) Copy   

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http://code.google.com/p/popcomm-ontology/

An ontology that models material entities, qualities, and processes related to collections of interacting organisms such as populations and communities. It is taxon neutral, and can be used for any species, including humans. The classes in the PCO are useful for describing evolutionary processes, organismal interactions, and ecological experiments. Practical applications of the PCO include community health care, plant pathology, behavioral studies, sociology, and ecology. The PCO is compliant with the Basic Formal Ontology (BFO) and is designed to be compatible with other OBO Foundry ontologies, such as the Gene Ontology (GO), which covers biological processes, and the Phenotypic Quality Ontology (PATO).

Proper citation: Population and Community Ontology (RRID:SCR_003462) Copy   

•   Source: SciCrunch Registry

http://wiki.cns.org

Wiki dedicated to neurosurgical topics, maintained by the Congress of Neurological Surgeons. Members can log in to contribute by adding or editing an article. A wiki is a collaborative technology for organizing information. Visitors can add, remove, and edit content. Like all other wikis, the CNS University's NeuroWiki allows linking among any number of pages. This ease of interaction and operation will engender collaborative authoring.

Proper citation: CNS NeuroWIki (RRID:SCR_003500) Copy   

•   Source: SciCrunch Registry