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http://neurolog.i3s.unice.fr/public_namespace/ontology

An ontology for neuroimaging or medical imaging studies based on DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering), as the foundational ontology. Detailed description from web: Our aim is the design of a common semantic model providing a unified view on all data and tools to be shared between NeuroLOG partners. For this purpose, we built a multi-layered and multi-components formal ontology. We chose a design framework that structures the ontology at different levels of abstraction while respecting common conceptualization choices. At the highest level is a top-level ontology that includes abstract concepts and relationships valid across domains. We adopted DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering), as the foundational ontology. We then added Core ontologies, which provide generic, basic and minimal concepts and relations in a specific domain. By minimal we mean that core ontologies should include only the most reusable and widely applicable categories. These kinds of ontologies are essential for sharing intended meaning between different domains. We adopted I& DA (Information and Discourse Acts), a core ontology initially built for classifying documents as a function of their content.We use it to model medical images, which we consider as types of documents. Participant Roles is the core ontology we use to describe the modes of image participation in data processing. I& DA and Participant Roles are built according to DOLCE ontological commitments. On the basis of these two layers, we constructed our Domain ontology dedicated to conceptualizing a specific domain, in this case neuroimaging. Obviously, large domains such as neuroimaging can be divided into sub-domains for the sake of modularization.

Proper citation: OntoNeuroLOG (RRID:SCR_008957) Copy   

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

Ontology for the description of drug discovery investigations. DDI aims to follow to the OBO (Open Biomedical Ontologies) Foundry principles, uses relations laid down in the OBO Relation Ontology, and be compliant with Ontology for biomedical investigations (OBI).

Proper citation: Ontology for Drug Discovery Investigations (RRID:SCR_010383) Copy   

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

Application ontology to model / represent the notion of genetic susceptibility to a specific disease or an adverse event or a pathological biological process. It is developed using BFO2.0''s framwork. The ontology is under the domain of genetic epidemiology.

Proper citation: Ontology for Genetic Susceptibility Factor (RRID:SCR_010386) Copy   

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http://purl.bioontology.org/ontology/ACGT-MO

Ontology to represent the domain of cancer research and management in a computationally tractable manner.

Proper citation: Cancer Research and Management ACGT Master Ontology (RRID:SCR_006953) Copy   

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

Ontology that describes the content of the models used in medical image simulation developed in the context of the Virtual Imaging Platform project (VIP), a french project aiming at sharing medical image simulation resources. This ontology can be used to annotate such models in order to highlight the different entities that are present in the 3D scene to be imaged, i.e. anatomical structures, pathological structures, foreign bodies, contrast agents etc. The model allows also to associate to these entities information about their physical qualities, which are used in the medical image simulation process (to mimick physical phenomena involved in CT, MR, US and PET imaging). This ontology partly relies on the OntoNeuroLOG ontology (ONL-DP ONL-MR-DA), as well as PATO, RadLex, FMA and ChEBI.

Proper citation: Medical image simulation (RRID:SCR_010355) Copy   

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http://purl.bioontology.org/ontology/ONL-MSA

Ontology that is a module of the OntoNeuroLOG ontology that covers the field of mental state assessments, i.e. instruments, instrument variables, assessments, and resulting scores, developed in the context of the NeuroLOG project, a french project aiming at integrating distributed heterogeous resources in neuroimaging. It includes a generic domain core ontology, that provides a general model of such entities and a general taxonomy of behavioural, neurosychological and neuroclinical instruments, that can be easily extended to model any particular kind of instrument. It also includes such extensions for 8 relatively standard instruments, namely: (1) the Beck-depression-inventory-(BDI-II), (2) the Expanded-Disability-Status-Scale, (3) the Controlled-oral-word-association-test, (4) the Free-and-Cued-Selective-Reminding-Test-with-Immediate-Recall-16-item-version-(The-Grober-and-Buschke-test), (5) the Mini-Mental-State, (6) the Stroop-color-and-word-test, (7) the Trail-making-test-(TMT), (8) the Wechsler-Adult-Intelligence-Scale-third-edition, (9) the Clinical-Dementia-Rating-scale, (10) the Category-verbal-fluency, (11) the Rey-Osterrieth-Complex-Figure-Test-(CFT).

Proper citation: Mental State Assessment (RRID:SCR_010357) Copy   

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

An ontology for metagenome sample metadata that mainly defines predicates.

Proper citation: Metagenome Sample Vocabulary (RRID:SCR_010358) Copy   

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https://cab.spbu.ru/software/spades/

Software package for assembling single cell genomes and mini metagenomes. Uses short read sets as input. Used for genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. Works with Illumina or IonTorrent reads and can provide hybrid assemblies using PacBio, Oxford Nanopore and Sanger reads. Intended for small genomes like bacterial or fungal., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SPAdes (RRID:SCR_000131) Copy   

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http://mindboggle.info/data.html

Complete set of free, publicly accessible, downloadable atlases, templates, and individual manually labeled brain image data, the largest collection of publicly available, manually labeled human brains in the world! http://journal.frontiersin.org/article/10.3389/fnins.2012.00171/full

Proper citation: Mindboggle-101 atlases (RRID:SCR_002439) Copy   

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

Symmetric atlas of the primate brain created using 18 cases of rhesus macaques aged 16-34 months. It includes the T1-weighted image (with and without skull), and also tissue segmentation probability maps (white matter, gray matter, CSF, rest), subcortical structures segmentation (amygdala, caudate, hippocampus, pallidus, putamen), and a lobar parcellation map. You can find more details about the creation of this atlas in the following paper : M. Styner, R. Knickmeyer, S. Joshi, C. Coe, S. J. Short, and J. Gilmore. Automatic brain segmentation in rhesus monkeys. In Proc SPIE Vol 6512, Medical Imaging, 2007, pp. 65122 L1-8

Proper citation: UNC Primate Brain Atlas (RRID:SCR_002570) Copy   

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http://www.med.unc.edu/bric/ideagroup/free-softwares/unc-infant-0-1-2-atlases

3 atlases dedicated for neonates, 1-year-olds, and 2-year-olds. Each atlas comprises a set of 3D images made up of the intensity model, tissue probability maps, and anatomical parcellation map. These atlases are constructed with the help of state-of-the-art infant MR segmentation and groupwise registration methods, on a set of longitudinal images acquired from 95 normal infants (56 males and 39 females) at neonate, 1-year-old, and 2-year-old.

Proper citation: UNC Infant 0-1-2 Atlases (RRID:SCR_002569) Copy   

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

A 3D stereoscopic (anaglyph method) full brain functional connectivity atlas created using a parcellation atlas published by Craddock et al. (2012). Using 3D Slicer 3.6.3 and the two hundred Region of Interest (ROI) version of the Craddock atlas, 200 grayscale surface models were created using a z-stat threshold > 2.3, and each surface model was processed with a surface decimation algorithm, smoothed with the Taubin algorithm and without surface normals. For improved visualization of the functional connectivity networks and their relative anatomical position, the surface model of five subcortical anatomical structures (corpus callosum, bilateral caudate, pallidum, putamen, thalamus, amygdala and hippocampus) were included in SAIBN. These surfaces were created with 3D Slicer using the segmentation computed with Freesurfer v. 5.1. The viewer should use red-cyan glasses to see the 3D stereoscopic effect using 3D Slicer (version 3.6.3, http://www.slicer.org/pages/Special:SlicerDownloads).

Proper citation: Stereoscopic Atlas of Intrinsic Brain Networks (RRID:SCR_002568) Copy   

•   Source: SciCrunch Registry

http://zebrafinch.brainarchitecture.org/

Atlas of high resolution Nissl stained digital images of the brain of the zebra finch, the mainstay of songbird research. The cytoarchitectural high resolution photographs and atlas presented here aim at facilitating electrode placement, connectional studies, and cytoarchitectonic analysis. This initial atlas is not in stereotaxic coordinate space. It is intended to complement the stereotaxic atlases of Akutegawa and Konishi, and that of Nixdorf and Bischof. (Akutagawa E. and Konishi M., stereotaxic atalas of the brain of zebra finch, unpublished. and Nixdorf-Bergweiler B. E. and Bischof H. J., A Stereotaxic Atlas of the Brain Of the Zebra Finch, Taeniopygia Guttata, http://www.ncbi.nlm.nih.gov.) The zebra finch has proven to be the most widely used model organism for the study of the neurological and behavioral development of birdsong. A unique strength of this research area is its integrative nature, encompassing field studies and ethologically grounded behavioral biology, as well as neurophysiological and molecular levels of analysis. The availability of dimensionally accurate and detailed atlases and photographs of the brain of male and female animals, as well as of the brain during development, can be expected to play an important role in this research program. Traditionally, atlases for the zebra finch brain have only been available in printed format, with the limitation of low image resolution of the cell stained sections. The advantages of a digital atlas over a traditional paper-based atlas are three-fold. * The digital atlas can be viewed at multiple resolutions. At low magnification, it provides an overview of brain sections and regions, while at higher magnification, it shows exquisite details of the cytoarchitectural structure. * It allows digital re-slicing of the brain. The original photographs of brain were taken in certain selected planes of section. However, the brains are seldom sliced in exactly the same plane in real experiments. Re-slicing provides a useful atlas in user-chosen planes, which are otherwise unavailable in the paper-based version. * It can be made available on the internet. High resolution histological datasets can be independently evaluated in light of new experimental anatomical, physiological and molecular studies.

Proper citation: Zebrafinch Brain Architecture Project (RRID:SCR_004277) Copy   

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http://cmrm.med.jhmi.edu/cmrm/atlas/human_data/file/JHUtemplate_newuser.html

DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention.

Proper citation: DTI White Matter Atlas (RRID:SCR_005279) Copy   

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http://www.dartmouth.edu/~rswenson/Atlas/

On line labeled atlas of the human brain developed by Dr. Rand Swenson of Dartmouth Medical School. It includes gross anatomical and MRI-generated slices (Axial T1-weighted MRI and Coronal T2 MRI weighted, along with Magnetic resonance arteriogram (MRA) and Magnetic resonance venogram (MRV)images. Labels may be turned on and off. A companion on-line textbook is also available. The site says it is still under construction, although the copyright is 2009. * Atlas of Gross Brain Topography * Atlas of the Brain Stem in Cross Section * Atlas of the Brain in Axial Slices * Atlas of the Brain in Coronal Slices * Atlas of the Head in Axial Slices * Axial T1-weighted MRI * Axial T2-weighted MRI * Coronal T1 MRI * Coronal T2 MRI * Magnetic resonance arteriogram (MRA) * Magnetic resonance venogram (MRV)

Proper citation: Atlas of the Brain (RRID:SCR_005967) Copy   

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http://www.civm.duhs.duke.edu/neuro2012ratatlas/

Multidimensional atlas of the adult Wistar rat brain based on magnetic resonance histology (MRH). The atlas has been carefully aligned with the widely used Paxinos-Watson atlas based on optical sections to allow comparisons between histochemical and immuno-marker data, and the use of the Paxinos-Watson abbreviation set. Our MR atlas attempts to make a seamless connection with the advantageous features of the Paxinos-Watson atlas, and to extend the utility of the data through the unique capabilities of MR histology: a) ability to view the brain in the skull with limited distortion from shrinkage or sectioning; b) isotropic spatial resolution, which permits sectioning along any arbitrary axis without loss of detail; c) three-dimensional (3D) images preserving spatial relationships; and d) widely varied contrast dependent on the unique properties of water protons. 3D diffusion tensor images (DTI) at what we believe to be the highest resolution ever attained in the rat provide unique insight into white matter structures and connectivity. The 3D isotropic data allow registration of multiple data sets into a common reference space to provide average atlases not possible with conventional histology. The resulting multidimensional atlas that combines Paxinos-Watson with multidimensional MRH images from multiple specimens provides a new, comprehensive view of the neuroanatomy of the rat and offers a collaborative platform for future rat brain studies. To access the atlas, click view supplementary materials in CIVMSpace at the bottom of the following webpage.

Proper citation: Adult Wistar Rat Atlas (RRID:SCR_006288) Copy   

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

An ontology consisting of two main components, an ontology of behavioral processes and an ontology of behavioral phenotypes. The behavioral process branch of NBO contains a classification of behavior processes complementing and extending the GO process ontology. The behavior phenotype branch of NBO consists of a classification of both normal and abnormal behavioral characteristics of organisms. The prime application of NBO is to provide the vocabulary that is required to integrate behavior observations within and across species. It is currently being applied by several model organism communities as well as in the description of human behavior-related disease phenotypes. The main ontology is available in both the OBO Flatfile Format and the Web Ontology Language (OWL).

Proper citation: Neurobehavior Ontology (RRID:SCR_006201) Copy   

•   Source: SciCrunch Registry

http://www.wiki-health.org/about/overview.php

WikiHealth is a collaborative online health and wellness community where your participation makes a difference! WikiHealth''s goal is to offer the most comprehensive, current and insightful information to help anyone and everyone achieve optimal health. Our belief is that your knowledge matters--- and you can help others by sharing what you know. WikiHealth is a collaborative writing project aiming to build an extensive and valueable repository on a variety of health and wellness topics. Our mission is to bring free, accesible and thorough information on health and wellness into the homes of every individual worldwide. The goal is for new articles on any health and wellness topic to be added regularly and for existing articles to be improved by volunteer contributors. In time, we envision WikiHealth to be the best health resource to come to for unbiased information as well as prescriptive advice on any health or wellness topic. Please join us by writing a new article or editing an existing one.

Proper citation: WikiHealth (RRID:SCR_004381) Copy   

•   Source: SciCrunch Registry

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

Ontology that provides a reference for describing an exercise in terms of functional movements, engaged musculoskeletal system parts, related equipment or monitoring devices, intended health outcomes, as well as target ailments for which the exercise might be employed as a treatment or preventative measure.

Proper citation: Ontology of Physical Exercises (RRID:SCR_003836) Copy   

•   Source: SciCrunch Registry

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

A structured controlled vocabulary of stage-specific anatomical structures of the human. It has been designed to mesh with the mouse anatomy and incorporates each Carnegie stage of development (CS1-20). The timed version of the human developmental anatomy ontology gives all the tissues present at each Carnegie Stage (CS) of human development (1-20) linked by a part-of rule. Each term is mentioned only once so that the embryo at each stage can be seen as the simple sum of its parts. Users should note that tissues that are symmetric (e.g. eyes, ears, limbs) are only mentioned once.

Proper citation: Human Developmental Anatomy Ontology timed version (RRID:SCR_010338) Copy   

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