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

A reference ontology that models the life cycle stage details of various parasites, including Trypanosoma sp., Leishmania major, and Plasmodium sp., etc. In addition to life cycle stages, the ontology also models necessary contextual details, such as host information, vector information, and anatomical location. OPL is based on the Basic Formal Ontology (BFO) and follows the rules set by the OBO Foundry consortium.

Proper citation: Ontology for Parasite LifeCycle (RRID:SCR_003427) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/ontology-for-genetic-interval/

An ontology that formalized the genomic element by defining an upper class genetic interval using BFO as its framework. The definition of genetic interval is the spatial continuous physical entity which contains ordered genomic sets (DNA, RNA, Allele, Marker,etc.) between and including two points (Nucleic_Acid_Base_Residue) on a chromosome or RNA molecule which must have a liner primary sequence structure.

Proper citation: Ontology for Genetic Interval (RRID:SCR_003423) Copy   

•   Source: SciCrunch Registry

http://wikihealthcare.jointcommission.org/bin/view/Home/WebHome

WikiHealthCare is The Joint Commission''s interactive forum for health care professionals. It is designed to enable and encourage discussion and collaboration among all users for the purpose of improving health care quality. While The Joint Commission provides the forum, users of the site control its content. The WikiHealthCare Quality Improvement forum is a collaborative network for health care professionals, researchers, and other health care stakeholders. Within this forum, you can freely exchange information, describe your implementation experiences and create and share performance improvement solutions. Registered members of the WikiHealthCare community are free to use this forum to create new web pages, initiate blogs, and dialogue with other members of the community.

Proper citation: WikiHealthCare (RRID:SCR_004474) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

Ontology as a basis for shared semantics and interoperability of simulations, of models, of algorithms and of other resources in this domain. The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles.

Proper citation: Human Physiology Simulation Ontology (RRID:SCR_010340) Copy   

•   Source: SciCrunch Registry

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

Ontology of logical observation identifier names and codes (LOINC); Version 2.26; January 2, 2009

Proper citation: Logical Observation Identifier Names and Codes (RRID:SCR_010341) Copy   

•   Source: SciCrunch Registry

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

Ontology for livestock reproductive traits and phenotypes

Proper citation: Reproductive Trait and Phenotype Ontology (RRID:SCR_006245) Copy   

•   Source: SciCrunch Registry

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

DICOM Controlled Terminology (PS3.16 2013 Annex D)

Proper citation: DICOM Controlled Terminology (RRID:SCR_010302) Copy   

•   Source: SciCrunch Registry

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

A computational diagnostic ontology containing 91 elements, including classes and sub-classes, which are required to conduct SR-MA (Systematic Review - Meta Analysis) for diagnostic studies, that will assist in standardized reporting of diagnostic articles. They also report high percentage of agreement among five observers as a result of the inter-observer agreement that they conducted among them to tag 13 articles using the diagnostic ontology. Moreover, they extend their existing repository CERR-N (Center of Excellence in Research Reporting in Neurosurgery) to include diagnostic studies.

Proper citation: Diagnostic Ontology (RRID:SCR_010307) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/BP-METADATA

Ontology that represents the structure that BioPortal uses to represent all of its metadata (ontology details, mappings, notes, reviews, views)

Proper citation: BioPortal Metadata Ontology (RRID:SCR_010167) Copy   

•   Source: SciCrunch Registry

https://www.amazon.com/How-Brain-Works-Mark-Dubin/dp/0632044411

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Is the Brain (Like) a Computer is an e-book written by Prof. Mark Dubin. It consists of the following: Introduction. Why do we consider the relationship of brains and computers and what does this have to do with consciousness? What's a Brain Made Of? A thought experiment. Test Drive a Turing Machine. A theoretical approach. Interim Summary. Many of the main pages have links to additional information. When you click on one of those links a NEW page will open ON TOP of the page you are clicking from. This convention is adopted so that you can look at the additional information and then easily return to the main page you got there from.

Proper citation: Is the Brain (Like) a Computer (RRID:SCR_008809) Copy   

•   Source: SciCrunch Registry

http://mendelspod.com/

A collection of content, including podcasts and blogs, to advance life science research, connecting people and ideas in the life sciences. Mendelspod creates a space for probing conversations and deep insight into the topics and trends which shape the industry''s future and therefore our future as a species. The podcasts are engaging, thoughtful thirty minute shows twice a week on highly relevant topics to those working around the life sciences. Their format enables them to go in depth with scientists who are leaders in their field, or CEOs of high growth companies to explore trends and the latest technologies. At Mendelspod, they offer a front row seat to the revolution going on in biology, putting a human face on some complicated, highly technical topics. Here you can tune in to hear Steve Burrill give his ''state of the industry'' overview, or listen to George Church talk about art and science, or find out how the latest developments in NGS are helping in the war on cancer. The blogs cover the latest trends and products, and can be entertaining. Guest bloggers featured and welcomed.

Proper citation: Mendelspod (RRID:SCR_009027) Copy   

•   Source: SciCrunch Registry

https://web.njit.edu/~matveev/calc.html

A modeling tool for simulating intracellular calcium diffusion and buffering. CalC solves continuous reaction-diffusion PDEs describing the entry of calcium into a volume through point-like channels, and its diffusion, buffering and binding to calcium receptors. Its features include: being platform-independent; being operated by simple script; combinable with MATLAB; and providing real-time views. Demos and manuals are provided on the website.

Proper citation: CalC (RRID:SCR_014259) Copy   

•   Source: SciCrunch Registry

https://code.google.com/archive/p/edlut/

Simulation software which creates spiking cell models using either a time-driven strategy or an event-driven strategy based on look-up tables. EDLUT serves as a tool for studying the computational principles of neural systems to reveal how different functionalities of the brain and central nervous system are based on cell and topology properties.

Proper citation: EDLUT (RRID:SCR_014261) Copy   

•   Source: SciCrunch Registry

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

A high level patient-centric ontology for the pharmaceutical industry. The ontology should enable silos in discovery research, hypothesis management, experimental studies, compounds, formulation, drug development, market size, competitive data, population data, etc. to be brought together. This would enable scientists to answer new questions, and to answer existing scientific questions more quickly. This will help pharmaceutical companies to model patient-centric information, which is essential for the tailoring of drugs, and for early detection of compounds that may have sub-optimal safety profiles. The ontology should link to existing publicly available domain ontologies.

Proper citation: Translational Medicine Ontology (RRID:SCR_010439) Copy   

•   Source: SciCrunch Registry

http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:DelPhi

DelPhi provides numerical solutions to the Poisson-Boltzmann equation (both linear and nonlinear form) for molecules of arbitrary shape and charge distribution. The current version is fast, accurate, and can handle extremely high lattice dimensions. It also includes flexible features for assigning different dielectric constants to different regions of space and treating systems containing mixed salt solutions. DelPhi takes as input a coordinate file format of a molecule or equivalent data for geometrical objects and/or charge distributions and calculates the electrostatic potential in and around the system, using a finite difference solution to the Poisson-Boltzmann equation. DelPhi is a versatile electrostatics simulation program that can be used to investigate electrostatic fields in a variety of molecular systems. Features of DelPhi include solutions to mixtures of salts of different valence; solutions to different dielectric constants to different regions of space; and estimation of the best relaxation parameter at run time.

Proper citation: DelPhi (RRID:SCR_008669) Copy   

•   Source: SciCrunch Registry

http://human-phenotype-ontology.github.io/

The Disease Ontology group has developed a set of standard representations of phenotypes associated with diseases useful in bioinformatics applications. These are formalized into an ontological structure and are encoded in OWL. Neurodegenerative diseases have a wide and complex range of biological and clinical symptoms. While neurodegenerative diseases share many pathological features in common, they also contain unique signatures. Animal models of these disorders are key to translational research. However, animal models typically replicate only a subset of disease features or display features that are only indirectly related to a given disorder, whose relationship to the human condition may be across several diseases. Matching animal models to human diseases is therefore a significant informatics challenge. We have been working to develop ontologies that capture essential features of neurodegenerative diseases and associated animal models in a way that allows more flexible matching of animal models to human disorders and in a way that makes explicit commonalities and differences among animal models and human neurodegenerative disease. Creating ontologies for diseases and disorders is a very challenging task (Gupta et al., 2003) because of the complexity of the disorders and because of the limitations of current ontology formalisms. In order to simplify the approach and make it practical for use in information systems, we have focused on formal descriptions of phenotypes associated with diseases and animal models rather than on a formal model of the disease process itself. We employ the modular ontologies developed as part of the Neuroscience Information Framework (NIF: http://nif.nih.gov) and the Phenotype and Trait Ontology (PATO), an ontology of qualities associated with biological phenotypes, to create a flexible template for creating phenotypic statements at the class and instance levels. We show how these phenotypes can be used to look for commonalities across multiple neurodegenerative conditions and animal models.

Proper citation: Disease Phenotype Ontology (RRID:SCR_008687) Copy   

•   Source: SciCrunch Registry