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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   

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http://www.wheaton.com

Wheaton Industries Inc. is a leading marketer, manufacturer and re-packager of containers, laboratory ware, instrumentation and associated products and services sold principally to customers in the general laboratory, life sciences, and diagnostics and reagent / chemicals packaging markets. Our products and services are marketed and sold globally through two divisions. The laboratory research products are sold through Wheaton Science Products, and the packaging products are sold through Wheaton Science Packaging.

Proper citation: Wheaton Industry Inc (RRID:SCR_008565) Copy   

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http://www.randomizer.org

This site is designed for researchers and students who want a quick way to generate random numbers or assign participants to experimental conditions. Research Randomizer can be used in a wide variety of situations, including psychology experiments, medical trials, and survey research. The program uses a JavaScript random number generator to produce customized sets of random numbers. Since its release in 1997, Research Randomizer has been used to generate number sets over 10.7 million times. This service is part of Social Psychology Network and is fast, free, and runs with any recent web browser as long as JavaScript isn''t disabled. Research Randomizer is a free service offered to students and researchers interested in conducting random assignment and random sampling. By using this service, you agree to abide by the SPN User Policy and to hold Research Randomizer and its staff harmless in the event that you experience a problem with the program or its results. Although every effort has been made to develop a useful means of generating random numbers, Research Randomizer and its staff do not guarantee the quality or randomness of numbers generated. Any use to which these numbers are put remains the sole responsibility of the user who generated them. What are the system requirements needed to run Research Randomizer? This program works best with Firefox and other recent web browsers. If you''re using a browser that came with America Online, or older browsers made prior to 2003, you may experience some difficulties with Research Randomizer. You may also not be able to use Research Randomizer with some limited-function browsers that do not fully support JavaScript, such as the Opera broswer used on certain game consoles. We would suggest that you update to a fairly recent, fully- functional stand-alone browser. How do I know what browser I am using? The easiest way to find this out is to click Help on the pulldown menu at the top of the screen. One of the options should be About Mozilla Firefox, About Internet Explorer, About Netscape, or something similar. Selecting this option will open a window that displays the name, version number, and copyright date of your browser. How does Research Randomizer generate its numbers? Research Randomizer uses the Math.random method within the JavaScript programming language to generate its random numbers for all modern web browsers. If you are using an older version of Microsoft Internet Explorer or Netscape Navigator (that is prior to version 4.0 of either), Research Randomizer uses an adaptation of the Central Randomizer by Paul Houle. Note that Research Randomizer no longer supports much-older browsers by other vendors (e.g., Mosaic). Who designed Research Randomizer? The original idea and programming for Research Randomizer came from Geoffrey C. Urbaniak in 1997. Research Randomizer was then jointly developed with Scott Plous, webmaster of Social Psychology Network, and online tutorials were added to the main program. In 1999 the site was redesigned with the assistance of Mike Lestik, in 2003 Mike Lestik added the download function, and in 2007 Mike Lestik and Scott Plous redesigned the site and added new content.

Proper citation: Research Randomizer (RRID:SCR_008563) Copy   

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http://www.ariad.com/

Cambridge, Massachusetts-based biotechnology company focused on cancer. Focus areas are blood cancers and solid tumors. Compounds: ponatinib, AP26113, ridaforolimus and AP1903., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ARIAD (RRID:SCR_008559) Copy   

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http://psychiatry.stanford.edu/alzheimer/

Portal for gerontology research with a variety of clinical, research and educational programs, with the aim of improving the lives of those affected by Alzheimer's Disease and memory losses associated with normal aging. The Center investigates the nature of Alzheimer's Disease, its progression over time, its response to treatments, and problems patients and caregivers experience in dealing with the changes that occur. It also conducts studies that look at changes that occur over the course of normal aging and have a Normal Aging Brain Donor Program. The Aging Clinical Research Center puts out a newsletter that showcases various projects and includes informative articles on dementia.

Proper citation: Stanford/VA Aging Clinical Research Center (RRID:SCR_008678) Copy   

•   Source: SciCrunch Registry

http://en.wikibooks.org/wiki/Main_Page

Community wiki for an open-content textbooks collection that anyone can improve or add to, start new books, and join project-related discussions in the reading rooms. Contributors maintain the property rights to their contributions, while the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License makes sure that the submitted version and its derivative works will always remain freely distributable and reproducible. Categories include: Computing, Engineering, Humanities, Languages, Mathematics, Miscellaneous, Science, Social sciences, All subjects. Wikibooks has two sub-projects; Wikijunior which is aimed at children and the Cookbook which is a collection of recipes and culinary topics. * 2,440 books with 40,746 pages (March 2012)

Proper citation: Wikibooks (RRID:SCR_008799) Copy   

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http://www.med.upenn.edu/cndr/index.shtml

A research institution which conducts clinical research to understand brain dysfunction and degeneration in Alzheimer's disease (AD), Parkinson's disease (PD), Frontotemporal disease (FTD), Amyotrophic Lateral Sclerosis (ALS or Lou Gehrig's disease), and other age-related neurodegenerative disorders. This organization also houses a general training program that has a focus on drug discovery. This program teaches trainees in etiology, pathogenesis, and diagnosis and treatment of Alzheimer's disease, Parkinson's disease, frontotemporal dementias, motor neuron disease and related disorders. This program also trains Ph.D and M.D/Ph.D students, as well scientists, physicians, and veterinarians who have already completed their advanced degree and are looking for a postdoctoral research fellowship. The program is designed to give a solid background in basic and translational neuroscience, and related disciplines.

Proper citation: University of Pennsylvania Center for Neurodegenerative Disease Research (RRID:SCR_008798) Copy   

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http://www.pathonet.org

PathoNet is a virtual meeting place for pathologists from all over the world. They can use it as a virtual pathology laboratory in which they can exchange their views on their cases. Join us and share your experience. Special or rare cases maybe very useful in the diagnostic practice. Everybody who would like to use digital microscopy in human, veterinary or forensic pathology; in laboratory medicine, in human anatomy; in experimental research, and when teaching can benefit from this resource. Additionally, practicing physicians, students, tutors, experts and researchers can all contribute and benefit from PathoNet. Sponsors: This resource is supported by 3DHISTECH Ltd.

Proper citation: PATHONET (RRID:SCR_008674) Copy   

•   Source: SciCrunch Registry

http://www.muschealth.com/multimedia/Podcasts/index.aspx?type=main

The MUSChealth.com Podcast Library, featuring podcasts on a variety of topics related to your health and our services here at MUSC. These medical podcasts are hosted by MUSC faculty, physicians and special guests and are produced and directed by Linda Austin, M.D. Current topics include: * Academics and Education * Aging, Geriatrics and Caregiving * Alcohol and Drug Dependency * Allergies and Asthma * Ashley River Tower * Bones, Joints, Muscles and Spine * Cancer * Children''s Health * Cosmetic Surgery * Dental * Dermatology/Skin Problems * Diabetes, Endocrinology and Metabolism * Digestive Health * ENT: Ear, Nose and Throat * Executive Health * Eye Health * General Health and Wellness * Heart and Vascular Health * Hospice * Kohl''s Take a Minute for Kids * Lungs and Breathing * Men''s Health * Mental Health * MUSC News and Events * Neurological Health * Organ Transplant * Osteoporosis * Pregnancy - Week by Week * Pregnancy and Childbirth * Radiology * Research and Clinical Trials * SC Health, Leadership and Policy * Sports Medicine * Stroke * Urology * Weight Loss Surgery Follow-up * Weight Management * Women''s Health

Proper citation: MUSC Health Podcast Library (RRID:SCR_008827) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/patentdata/

Patent data resources at the EBI contain patent abstracts, patent chemical compounds, patent sequences and patent equivalents. There are various ways of accessing and searching the patent data.

Proper citation: Patent Data Resources (RRID:SCR_008708) Copy   

•   Source: SciCrunch Registry

http://grey.colorado.edu/emergent

emergent is a comprehensive, full-featured neural network simulator that allows for the creation and analysis of complex, sophisticated models of the brain in the world. With an emphasis on qualitative analysis and teaching, it also supports the workflow of professional neural network researchers. Its high level drag-and-drop programming interface, built on top of a scripting language that has full introspective access to all aspects of networks and the software itself, allows one to write programs that seamlessly weave together the training of a network and evolution of its environment without ever typing out a line of code. Networks and all of their state variables are visually inspected in 3d, allowing for a quick visual regression of network dynamics and robot behavior. This same 3d world sports a highly accurate Newtonian physics simulation, allowing you to create rich robotics simulations (for example, a car). As a direct descendant of PDP (1986) and PDP (1999), emergent has been in development for decades. In the most recent versions available strive to distill it down to its essential elements. Those that take the time to learn the best practices will be rewarded with the ability to create and understand the most complicated neural models ever published.

Proper citation: Emergent (RRID:SCR_008500) Copy   

•   Source: SciCrunch Registry

http://www.neuroanatomy.ca/

The WEB ATLAS contains photographs of dissected brains showing important structures. The diagrams folder contains drawings showing functionally important parts of the brain as well as drawings of dissections adapted from C.G. Smith. We are particularly pleased to make Nan Cheney''s medical illustrations of the brain and the head available. The STROKE MODEL portion of the website has syndromes associated with strokes of different vessels of the brain as well as extensive diagrams and tables about the vessels of the brain. The 3D RECONSTRUCTIONS featured on this website were made from MRI scans through the brain - where indicated the source material was from the NIH Visible Human Project. The website will also contain material important for the neuroanatomy labs for med students at UBC. Weekly quizzes will help you keep up with studying the material, the podcasts will help you review material presented in the labs, and the weekly wikis will help you share information with your peers.

Proper citation: Neuroanatomy at UBC (RRID:SCR_008744) Copy   

•   Source: SciCrunch Registry

http://amser.org./index.php?P=AMSER--About

AMSER is a portal of educational resources and services built specifically for use by those in Community and Technical Colleges but free for anyone to use. AMSER provides links to resources for faculty, staff, librarians, students and others for use in both educational settings or in their pursuit of life long learning. Sponsors: AMSER is funded by the National Science Foundation (NSF) as part of the National Science Digital Library, and is being created by a team of project partners led by Internet Scout.

Proper citation: Applied Math and Science Education Repository (RRID:SCR_008501) Copy   

•   Source: SciCrunch Registry

http://derisilab.ucsf.edu/

The DeRisi Lab focuses on genomic approaches to the study of infectious disease. Specifically, we are studying Plasmodium falciparum, the causative agent of the most deadly form of human malaria. We are also involved in a major effort for the discovery of new viral pathogens associated with diseases of unknown etiology. Software tools developed in the lab include: HMMSplicer discovers splice sites in high throughput sequencing datasets without using gene models. HMMSplicer can also be used to find non-canonical junctions as well. HMMSplicer was benchmarked on publickly available A. thaliana, H. sapiens, and P. falciparum datasets and performs well on all genomes. Information about the datasets tested, including the exact command parameters and the final results, is provided. HMMSplicer is implemented in Python and is freely available for all. VersaCount is a simple application to assist with the counting of cells by microscopy. When used with a numeric keypad, it can significantly increase counting efficiency when compared with a traditional clicker. Although it was designed for malaria work, it can be customized for a wide variety of cell counting applications. VersaCount was written by Charlie Kim. ExpressionNet is a program written by Jingchun Zhu that uses Bayesian network learning algorithms to explore relationships among random variables to generate network models. The software has been used to study the transcriptional response to environmental perturbations in budding yeast. Details of the program and the study of yeast transcription using Bayesian Networks was published in PLoS ONE. DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. ArrayOligoSelector (AOS) is an open source program developed by Jingchun Zhu for the purpose of systematically designing gene-specific long oligonucleotide probes for entire genomes. For each open reading frame, the program optimizes oligo selection based upon several parameters, including uniqueness, complexity, secondary structure, GC content, and 3'' end proximity. AOS also is hosted at SourceForge. This site contains documentation and a user-friendly how-to. ArrayMaker 2 provides high performance robotic control of microarrayer robots with an incredibly intuitive, easy to use interface. ArrayMaker 2 is optimized for use with the new generation of ultra fast linear servo driven arrayers, yet it is backwards compatible with the original MGuide style of ball-screw driven arrayers.

Proper citation: DeRisi Lab (RRID:SCR_008581) Copy   

•   Source: SciCrunch Registry

http://www.textpresso.org/

An information extracting and processing package for biological literature that can be used online or installed locally via a downloadable software package, http://www.textpresso.org/downloads.html Textpresso's two major elements are (1) access to full text, so that entire articles can be searched, and (2) introduction of categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., methods, etc). A search engine enables the user to search for one or a combination of these categories and/or keywords within an entire literature. The Textpresso project serves the biological and biomedical research community by providing: * Full text literature searches of model organism research and subject-specific articles at individual sites. Major elements of these search engines are (1) access to full text, so that the entire content of articles can be searched, and (2) search capabilities using categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or identify one (e.g., cell, gene, allele, etc). The search engines are flexible, enabling users to query the entire literature using keywords, one or more categories or a combination of keywords and categories. * Text classification and mining of biomedical literature for database curation. They help database curators to identify and extract biological entities and facts from the full text of research articles. Examples of entity identification and extraction include new allele and gene names and human disease gene orthologs; examples of fact identification and extraction include sentence retrieval for curating gene-gene regulation, Gene Ontology (GO) cellular components and GO molecular function annotations. In addition they classify papers according to curation needs. They employ a variety of methods such as hidden Markov models, support vector machines, conditional random fields and pattern matches. Our collaborators include WormBase, FlyBase, SGD, TAIR, dictyBase and the Neuroscience Information Framework. They are looking forward to collaborating with more model organism databases and projects. * Linking biological entities in PDF and online journal articles to online databases. They have established a journal article mark-up pipeline that links select content of Genetics journal articles to model organism databases such as WormBase and SGD. The entity markup pipeline links over nine classes of objects including genes, proteins, alleles, phenotypes, and anatomical terms to the appropriate page at each database. The first article published with online and PDF-embedded hyperlinks to WormBase appeared in the September 2009 issue of Genetics. As of January 2011, we have processed around 70 articles, to be continued indefinitely. Extension of this pipeline to other journals and model organism databases is planned. Textpresso is useful as a search engine for researchers as well as a curation tool. It was developed as a part of WormBase and is used extensively by C. elegans curators. Textpresso has currently been implemented for 24 different literatures, among them Neuroscience, and can readily be extended to other corpora of text.

Proper citation: Textpresso (RRID:SCR_008737) Copy   

•   Source: SciCrunch Registry

http://www.ctspedia.org/do/view/CTSpedia

CTSpedia is a national effort to collect wisdom, tools, educational materials, and other items useful for clinical and translational researchers and to provide timely and useful advice to clinical and translational researchers with specific problems. The CTSpedia is a collaborative vehicle for the CTSA''s Biostatistics/Epidemiology/Research/Design (BERD) Online Resources and Education taskforce to identify and share resources across the national consortium and community researchers world-wide. With the support of the national BERD consortia, the project obtained funding and support from the National Center for Research Resources (NCRR) to expand the original scope and content of CTSpedia and foster collaboration amongst CTSAs. The main goal of CTSpedia.org is to create a definable academic home on the internet for the discipline of clinical and translational sciences across the country and the world. * While the CTSA consortium serves the onsite physical level of the institutions involved, CTSpedia.org seeks to fill the gaps where the network is lacking, and to augment that network as the central hub for the peer to peer sharing of knowledge and resources. * While the CTSA national scope comes to fruition, the international scope of the consortia is more readily facilitated with an online resource like CTSpedia. * Utilizing the collaborative nature of the wiki-style website, CTSpedia.org allows for researchers anywhere in the world to ask questions and receive answers and related information in a timely and efficient manner, overcoming the logistical issues of distance and scheduling. * The streamlined availability of an online resource and knowledge repository will aid in addressing common issues that arise in clinical research, which will filter out consultation requests for minor questions, allowing for CTSA consultants to address more prevalent consultations.

Proper citation: CTSpedia (RRID:SCR_008733) Copy   

•   Source: SciCrunch Registry

http://www.nimblegen.com

Roche NimbleGen, Inc. is a leading innovator, manufacturer and supplier of a proprietary suite of DNA microarrays, consumables, instruments and services. Roche NimbleGen uniquely produces high-density arrays of long oligo probes that provide greater information content and higher data quality necessary for studying the full diversity of genomic and epigenomic variation. Roche NimbleGen is enabling a new era of High-Definition Genomics by providing scientists with cost-effective, high-throughput tools for extracting and integrating complex data on important forms of genomic and epigenomic variation not previously accessible on a genome-wide scale. Scientists can thus obtain a clearer understanding of genomic and epigenomic structure and function and how they impact biology and medicine. This improved performance is made possible by Roche NimbleGen''s proprietary Maskless Array Synthesis (MAS) technology, which uses digital light processing and rapid, high-yield photochemistry to synthesize long oligo, high-density DNA microarrays with extreme flexibility. NimbleGen Systems was established in 1999. The MAS technology is the result of research collaborations between the departments of biotechnology, genetics, physics, and semiconductor engineering at the University of Wisconsin - Madison. Roche NimbleGen has the exclusive worldwide license to the MAS technology from the Wisconsin Alumni Research Foundation (WARF).

Proper citation: Roche NimbleGen (RRID:SCR_008571) Copy   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=gma

Software package to perform Granger mediation analysis for time series. Includes single level GMA model and two-level GMA model, for time series with hierarchically nested structure.

Proper citation: GMA (RRID:SCR_009212) Copy   

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

An open-source C++-based application that allows automatic as well as user-interactive segmentation of the Corpus Callosum. Via a Qt-based graphical user interface, CCSeg also performs semi-automatic segmentation.

Proper citation: CCSeg - Corpus Callosum Segmentation (RRID:SCR_009453) Copy   

•   Source: SciCrunch Registry

http://crezoo.crt-dresden.de/crezoo/

Database of helpful set of CreERT2 driver lines expressing in various regions of the developing and adult zebrafish. The lines have been generated via the insertion of a mCherry-T2A-CreERT2 in a gene trap approach or by using promoter fragments driving CreERT2. You can search the list of all transgenic lines or single entries by insertions (gene) or expression patterns (anatomy/region). In most cases the CreERT2 expression profile using in situ hybridization at 24 hpf and 48 hpf is shown, but also additional information (e.g. mCherry or CreERT2 expression at adult stages, transactivation of a Cre-dependent reporter line) is displayed. Currently, not all insertions have been mapped to a genomic location but the database will be regularly updated adding newly generated insertions and mapping information. Your help in improving and broadening the database by giving your opinion or knowledge of expression patterns is highly appreciated.

Proper citation: CreZoo (RRID:SCR_008919) Copy   

•   Source: SciCrunch Registry