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http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

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http://www.gene-regulation.com/pub/databases.html

In an effort to strongly support the collaborative nature of scientific research, BIOBASE offers academic and non-profit organizations free access to reduced functionality versions of their products. TRANSFAC Professional provides gene regulation analysis solutions, offering the most comprehensive collection of eukaryotic gene regulation data. The professional paid subscription gives customers access to up-to-date data and tools not available in the free version. The public databases currently available for academic and non-profit organizations are: * TRANSFAC: contains data on transcription factors, their experimentally-proven binding sites, and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. * TRANSPATH: provides data about molecules participating in signal transduction pathways and the reactions they are involved in, resulting in a complex network of interconnected signaling components.TRANSPATH focuses on signaling cascades that change the activities of transcription factors and thus alter the gene expression profile of a given cell. * PathoDB: is a database on pathologically relevant mutated forms of transcription factors and their binding sites. It comprises numerous cases of defective transcription factors or mutated transcription factor binding sites, which are known to cause pathological defects. * S/MARt DB: presents data on scaffold or matrix attached regions (S/MARs) of eukaryotic genomes, as well as about the proteins that bind to them. S/MARs organize the chromatin in the form of functionally independent loop domains gained increasing support. Scaffold or Matrix Attached Regions (S/MARs) are genomic DNA sequences through which the chromatin is tightly attached to the proteinaceous scaffold of the nucleus. * TRANSCompel: is a database on composite regulatory elements affecting gene transcription in eukaryotes. Composite regulatory elements consist of two closely situated binding sites for distinct transcription factors, and provide cross-coupling of different signaling pathways. * PathoSign Public: is a database which collects information about defective cell signaling molecules causing human diseases. While constituting a useful data repository in itself, PathoSign is also aimed at being a foundational part of a platform for modeling human disease processes.

Proper citation: Gene Regulation Databases (RRID:SCR_008033) Copy   

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http://www.dialog.com

Dialog provides critical information from the world''s most authoritative publishers, combined with the tools to search every bit of it with speed and precision. With direct operations in 27 countries, Dialog products and services are a combination of highly accurate online research tools offering access to unique and relevant databases designed to meet the specific needs of a wide range of users. Information professionals and end-users at business, professional, scientific, academic and government organizations in more than 100 countries prize Dialog services to meet their searching needs. As part of the Deep Web, which is estimated to be 500 times larger than the content accessible via Web search engines, Dialog products offer unparalleled depth and breadth of content coupled with the ability to search with precision and speed. Our collection of over 900 databases handles more than 700,000 searches and delivers over 17 million document page views per month. Searchable content on Dialog services includes articles and reports from thousands of real-time news feeds, newspapers, broadcast transcripts and trade publications, plus market research reports and analyst notes providing support for financial decision-making, as well as in-depth repositories of scientific and technical data, patents, trademarks and other intellectual property data. Additional content areas include government regulations, social sciences, food and agriculture, reference, energy and environment, chemicals, pharmaceuticals and medicine.

Proper citation: Dialog (RRID:SCR_008482) Copy   

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https://www.msu.edu/~brains/index.html

The Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. Atlases and brain sections are available for a variety of mammals, and we are also developing a series of labeled atlases of stained sections for educators, students, and researchers. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan. What we are doing currently at Michigan State is a series of demonstration projects for publicizing the contents of the collections and ways in which they can be used. For example, the images from the collection can be used for comparative brain study. We have prepared databases of the contents of the collections for presentation and use on this site, as well as for downloading by users in several formats. We are also developing a series of labeled atlases of stained sections for educators, students, and researchers. This internet site is associated with the Comparative Mammalian Brain Collections site. All of the images are in JPEG or GIF format.

Proper citation: Michigan State University Brain Biodiversity Bank (RRID:SCR_003289) Copy   

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https://moffitt.org/research-science/shared-resources/tissue/

A central tissue repository at Moffitt specializing in protocol-driven human tissue collection, storage, processing and dissemination. Tissue Core provides investigators with access to high quality, well-annotated human specimens obtained from representative of the patient populations. The advent of powerful molecular technologies has opened the door to developing more effective treatments of patients with cancer. Access to high quality specimens with associated clinical, treatment, recurrence outcome data will be critical to developing and validating the tests needed for diagnosis and prediction of response to therapy. Since its commencement in 1993, the Tissue Core has collected more than 8,000 cases of human liquid cancers and solid primary and metastatic tumors both malignant and benign with adjacent normal, from variety of sites and diagnoses. Collected samples are mostly remnant tissues obtained from patients undergoing therapeutic surgical procedures at the Center. The core also ensures tissue release compliance with USF-IRB and Privacy Board recommendations. * Protocol driven sample collection, processing and distribution * Collection of sample and patient demographic information. * Nucleic acid extractions from tissue sections, FNA, core biopsies blood and bone marrow. * Histology services: H&E slides, staining, sectioning, paraffin blocks, OCT blocks, sample microdissection * WBC, plasma and serum isolation. * Project development and support: Facility staff provides advice and guidance to researchers.

Proper citation: Moffitt Cancer Center Tissue Core (RRID:SCR_004406) Copy   

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http://scholarometer.indiana.edu/

Scholarometer (beta) is a social tool to facilitate citation analysis and help evaluate the impact of an author''s publications. It is a social (crowdsourcing) application that leverages the wisdom of the crowds. Scholarometer makes visualization of author and discipline networks available on the web site. It requires users to tag their queries with one or more discipline names, choosing from predefined ISI subject categories or arbitrary tags. This generates annotations that go into a database, which collects statistics about the various disciplines, such as average number of citations per paper, average number of papers per authors, etc. This data is publicly available. Scholarometer users can save the finding into formats appropriate for local reference management software (e.g., EndNote), or for social publication sharing systems (e.g., BibSonomy). Currently, our system supports the following export formats: BibTex (BIB), RefMan (RIS), EndNote (ENW), comma-separated values (CSV), tab-separated values (XLS), and BibJSON. Export data is dynamically generated in response to any filter, merge or delete actions performed by the user. Since Scholarometer is a browser extension that provides a smart interface for Google Scholar, it does not have the limitations of server based citation analysis tools that sit between the user and Google Scholar. At the same time Scholarometer is not an application, such as Publish or Perish, and therefore it is platform independent and runs on every system that supports the Firefox or the Chrome browser. Still, Scholarometer uses Google Scholar, which provides the most comprehensive source of citation data across the sciences and social sciences. Scholarometer provides a RESTful web API so that other developers can make use of our crowdsourced data. Select the method on the left panel to see corresponding documentation. The extension/add-on code is available in the Mozilla Firefox Add-ons and Google Chrome Extensions repositories. Additional server-side code is not available at this time.

Proper citation: Scholarometer (RRID:SCR_004279) Copy   

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http://manisnet.org/

MaNIS is a database and infrastructure meant to facilitate open access to combined specimen data from a web browser, enhance the value of specimen collections, conserve curatorial resources, and use a design paradigm that can be easily adopted by other disciplines with similar needs. With support from the National Science Foundation, seventeen North American institutions and their collaborators developed the Mammal Networked Information System. The original objectives of MaNIS were to 1) facilitate open access to combined specimen data from a web browser, 2) enhance the value of specimen collections, 3) conserve curatorial resources, and 4) use a design paradigm that can be easily adopted by other disciplines with similar needs. As an NSF-funded initiative, MaNIS has achieved these objectives while avoiding the need for long-term, external maintenance of the network and centralized data management. As MaNIS faces the future, it is only through expansion of the network, both nationally and internationally, that the real impact of this collaborative effort will be maximized. Participation by other institutions is now welcome and those wishing to join have at their disposal the data standards, software and documentation that were developed for this project. All that is asked of future participants is that they make the same institutional commitment as the original collaborators to maintain their repositories of high-quality specimen collections and make the accompanying data available for the benefit of all. At the time of its inception, development of MaNIS addressed the urgent call for natural history museums to come together to build and support a biodiversity informatics infrastructure to facilitate and enhance research, education, conservation, and public health. That call has now been answered. It is hoped that continued expansion of the network will allow the preservation and sustainable use of biodiversity in all its complexity as we attempt to address the magnitude of human impacts on the Earth''s ecological systems during the 21st century. Supported by NSF

Proper citation: Mammal Networked Information System (RRID:SCR_008332) Copy   

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http://www.michr.umich.edu/services/biorepository

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 24,2025. In 2009, the Medical School and the Michigan Institute for Clinical & Health Research (MICHR) unveiled a new biorepository for U-M researchers in need of a controlled storage environment for biological samples. MICHR is pleased to be able to add to its many services for the research community a centralized biological repository for controlled storage of biological samples, and related services (including DNA, RNA, and other downstream preparation) within the U-M campus. The biorepository, located in the CAP/CLIA-certified Michigan Center for Translational Pathology (MCTP) laboratory at the U-M Traverwood facility on Huron Parkway, will store biologic material, including blood and urine. Sample accessioning and tracking will be accomplished using the caTISSUE suite of programs, and samples will be processed and stored in compliance with CAP/CLIA guidelines. Initially, all samples will be used only with the authorization of the individual investigator who directed the project under which the samples were obtained. Samples will be used in accordance with the relevant informed consent. Long-term plans include federating the database in order to facilitate sharing of data and samples between research teams.

Proper citation: University of Michigan Biorepository (RRID:SCR_004643) Copy   

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https://clinicaltrials.gov/study/NCT01619475

Study consisting of nine liver transplant centers with expertise in adult living-donor liver transplantation (LDLT) and a central data coordinating center to provide valuable information on the outcomes of adult to adult living donor liver transplantation (AALDLT) to aid decisions made by physicians, patients, and potential donors. The study will establish and maintain the infrastructure required to accrue and follow sufficient numbers of patients being considered for and undergoing AALDLT to provide generalizable data from adequately powered studies. The major aims of A2ALL are as follows: * Quantify the impact of choosing LDLT on the candidate for transplantation * Characterize the difference between LDLT and deceased donor liver transplant (DDLT) in terms of post-transplant outcomes, including patient and graft survival, surgical morbidity, and resource utilization on the recipient of a transplant * Determine the short- and long-term health and quality of life (QOL) impact of donation, including (a) morbidity after liver donation and (b) long-term health-related QOL of donors. * Standardize and assess the role of informed consent in affecting the decision to donate and satisfaction after living liver donation * Other aims include comparison of the severity of recurrence of hepatocellular carcinoma for DDLT versus LDLT, the systematic characterization of liver regeneration and function in donors and recipients, the evaluation of the differences in the immune response to LDLT versus DDLT, and the establishment of a robust data and sample repository on liver transplantation that may be used to study clinical and biological questions as new technologies and resources become available. Patients enrolled in the study will be followed and managed in a standardized fashion.

Proper citation: Adult to Adult Living Donor Liver Transplantation Cohort Study (RRID:SCR_001494) Copy   

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https://github.com/cidvbi/PathogenPortal/wiki

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 4,2025. These centers support existing and newly developed techniques for bioinformatic analysis aimed at obtaining a deeper understanding of the fundamental biology of a specific set of pathogenic organisms, and efforts to counter the threats posed by these pathogens. The mission of the PathogenPortal is to showcase the collective efforts of the BRCs, and to make the efforts of each BRC more accessible. The PathogenPortal''s content is organized by BRC in both the menus at the top of each page, and the categories in the left column of most pages.. As part of the Pathogen Portal, we have established a Scientific Working Group (SWG) comprised of members with deep expertise in a broad range of domains of relevance to the Pathogen Portal. The SWG provides advice about the management and performance of the resource, and about the needs of the scientific community in relation to the resource. Sponsor. Pathogen Portal is a repository linking to four Bioinformatics Resource Centers (BRCs) sponsored by the National Institute of Allergy and Infectious Diseases (NIAID) and maintained by The Virginia Bioinformatics Institute. The BRCs are providing web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases

Proper citation: Pathogen Portal (RRID:SCR_008472) Copy   

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http://www.janelia.org/team-project/fly-em

A project producing datasets, software, and algorithms that is developing the technology to produce connectomes at the electron microscopic level of behaviorally-relevant neural circuits as well as the entire Drosophila nervous system. This technology will enable them to create a map of every neuron and synapse in the Drosophila nervous system, using novel approaches to electron microscopy (EM) as the foundation. In the same way that the fly genome paved the way for larger projects, including sequencing the human genome, Fly EM may ultimately contribute to our understanding of the human brain by establishing a fly "connectome" a map that shows how all neurons in the fly brain are connected to each other. They began their entry into EM reconstruction with the fly's adult visual system, where much is known about cell types from previous EM and histological studies, as well as ongoing studies in the Fly Light Project. In addition to establishing and publishing a fly connectome, Fly EM will make technology and methodology available that is needed to perform large-scale EM reconstructions. Fly EM will generally pursue an open policy with their datasets, software, and algorithms after relevant publications. When an EM reconstruction is published, the derived connectome and reconstructed neuronal skeletons will be made available online. The raw data and annotatations will be made available upon request as logistics dictate. To encourage further collaboration and scientific discovery, a small fraction of their raw data and corresponding segmentation will be made available independent of publication. Their goal is to enable others who wish to approach the many algorithmic challenges, but who do not have access to an EM facility, to have the data they need to support methods development, as well as their results to use as a benchmark. Fly EM emphasizes publication of supporting techniques and software approaches before major EM reconstruction releases to encourage rapid feedback from the community and adoption of their strategies. FlyEM maintains much of its software in the open-source repository GitHub:http://janelia-flyem.github.com. They will provide information on official release versions of these packages on git-hub when it reaches reasonable maturity.

Proper citation: Fly EM (RRID:SCR_002242) Copy   

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http://neuronalarchitects.com/ibiofind.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 17, 2016. C#.NET 4.0 WPF / OWL / REST / JSON / SPARQL multi-threaded, parallel desktop application enables the construction of biomedical knowledge through PubMed, ScienceDirect, EndNote and NIH Grant repositories for tracking the work of medical researchers for ranking and recommendations. Users can crawl web sites, build latent semantic indices to generate literature searches for both Clinical Translation Science Award and non-CTSA institutions, examine publications, build Bayesian networks for neural correlates, gene to gene interactions, protein to protein interactions and as well drug treatment hypotheses. Furthermore, one can easily access potential researcher information, monitor and evolve their networks and search for possible collaborators and software tools for creating biomedical informatics products. The application is designed to work with the ModelMaker, R, Neural Maestro, Lucene, EndNote and MindGenius applications to improve the quality and quantity of medical research. iBIOFind interfaces with both eNeoTutor and ModelMaker 2013 Web Services Implementation in .NET for eNeoTutor to aid instructors to build neuroscience courses as well as rare diseases. Added: Rare Disease Explorer: The Visualization of Rare Disease, Gene and Protein Networks application module. Cinematics for the Image Finder from Yale. The ability to automatically generate and update websites for rare diseases. Cytoscape integration for the construction and visualization of pathways for Molecular targets of Model Organisms. Productivity metrics for medical researchers in rare diseases. iBIOFind 2013 database now includes over 150 medical schools in the US along with Clinical Translational Science Award Institutions for the generation of biomedical knowledge, biomedical informatics and Researcher Profiles.

Proper citation: iBIOFind (RRID:SCR_001587) Copy   

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http://neuromarca.com/

A blog about neuromarketing, a research methodology born of the fusion of neuroscience and research techniques of conventional marketing in Spanish by Sergio Monge. If you want to read it in English, Google translate does a good job. A good way to learn about practical applications of neuroscience to a field with little exposure in conventional neuroscience academia. The neuromarketing is a branch of market research that uses biometric measurement systems in their studies (EEG, MRI, galvanic skin response, eye-tracking, heart rate ...). One of the most significant differences with conventional research neuromarketing is not content with the verbal statements of the subjects, but aims to go further, unraveling the effect of the unconscious and emotions in decision-making. The author of Neuromarca is Sergio Monge, Degree in Advertising and Public Relations and PhD in Audiovisual Communication and Advertising from the University of the Basque Country / Euskal Herriko Universitatea. Sergio has experience in the field of Corporate Communications and is familiar with the blogosphere and the Internet communication environment. He currently teaches full time for the UPV / EHU and offers some services such as communications and marketing consultant. The interest of the author of this blog by neuroscience and neuromarketing longstanding but his attendance Neuro Connections conference, held from 5 to 7 febreo 2009 in Krakow (Poland), is the main reason he began writing Neuromarca. The intention is that Neuromarca is a repository of articles in Spanish about neuromarketing, so that could be a reference to the Hispanic blogosphere in this emerging discipline.

Proper citation: Neuromarca (RRID:SCR_006236) Copy   

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http://xoonips.sourceforge.jp/

Neuroinformatics (NI) is a new discipline that challenges the understanding of the structure and mechanism of the brain by combining neuroscience and information technology. The global collaborations in this field have been actively started with the support of the International Neuroinformatics Coordinating Facility (INCF) launched in November 2005. The Laboratory for Neuroinformatics at RIKEN Brain Science Institute (BSI) is involved in developing various cutting-edge technologies related to NI such as XooNIps. XooNIps succeeded the concept and basic feature of the vision science platform; Visiome, constructed by the NRV (i.e., Neuroinformatics Research in Vision) Project and has been developed based on a content management system (CMS); XOOPS, as infrastructure for NI databases to share different types of data on the Internet. :XooNIps has three features: :The first is the flexibility of developing databases. CMS-based XooNIps makes it easy to change the design or to extend the functions of databases by combining the different modules available on XOOPS. Therefore, even those who are not expert in computer system can develop their database on XooNIps. :The second is the diversity and extensibility of the data which can be handled by XooNIps. In order to handle different types of actual data, it provides not only the various data forms per se, but also the extension method to handle a new data form, which enables to deal easily with even a non-standardized data form. :The third is the facility to distribute metadata. XooNIps implements OAI-PMH (i.e., Open Archive Initiative-Protocol for Metadata Harvesting) which is one of the standard protocols to distribute metadata. This enables to collect information on other databases which are developed on XooNIps or to coordinate databases by exchanging metadata with other databases which implement OAI-PMH than those on XooNIps. :Since April 2007, Neuroinformatics Japan Center (NIJC) at RIKEN BSI takes charge of extending and maintaining XooNIps, and is committed to manage the documentation hereafter. :NIJC, as a national node of INCF, is developing and operating various NI platforms in neuroscience based on XooNIps to establish and facilitate NI research in Japan. XooNIps is also being applied to databases or organizational repositories in several institutions and universities, and laboratory groupware in various fields. We hope XooNIps will be of universal use in and out of Japan. :database; binary executable; software development tool; metadata; data set; :

Proper citation: XooNIps - Neuroinformatics Base Platform System (RRID:SCR_013590) Copy   

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http://www.usidnet.org/

Research consortium to advance scientific research in the primary immune deficiency diseases (PIDD) and: * Assemble and maintain a registry of patients with primary immunodeficiency diseases to provide a minimum estimate of the prevalence of each disorder in the United States. Provide a comprehensive clinical picture of each disorder and act as a resource for clinical and laboratory research. * Establish a multifaceted mentoring program to introduce new investigators into the field and stimulate interest and research in primary immune deficiency diseases. * Establish an advisory/review committee to maintain a cell/DNA Repository of biologic material from well-characterized PIDD patients for the advancement of scientific research USIDNET operates a large database of patient information for your use. The purpose and scope of this project is to assemble and maintain a registry of residents with primary immunodeficiency diseases. The project was started with the Registry of U.S. Residents with Chronic Granulomatous Disease. Since then, the registry has been expanded and now collects data on all primary immunodeficiency disorders. The following are just a few of the diseases housed in the registry: Chronic Granulomatous Disease, Common Variable Immunodeficiency Disease, DiGeorge Anomaly, Hyper IgM Syndrome, Leukocyte Adhesion Defect, Severe Combined Immunodeficiency Disease, Wiskott-Aldrich Syndrome, X-Linked Agammaglobulinemia Physicians who would like to register their patients or access the registry are encouraged to contact Onika Davis or Lamar Hamilton, USIDNET team, at odavis (at) primaryimmune.org, or lhamilton (at) primaryimmune.org

Proper citation: USIDNET: US Immunodeficiency Network (RRID:SCR_004672) Copy   

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http://www.uwstructuralgenomics.org/

It is a specialized research center supported by the Protein Structure Initiative (PSI) of the National Institute of General Medical Sciences (NIGMS), one of the National Institutes of Health (NIH). PSI is a federal, university, and industry effort aimed at dramatically reducing the costs and lessening the time it takes to determine a three-dimensional protein structure. The long-range goal of PSI is to solve 10,000 protein structures in 10 years and to make the three-dimensional atomic-level structures of most proteins easily obtainable from knowledge of their corresponding DNA sequences. CESG is located within the Department of Biochemistry at the University of Wisconsin-Madison (Madison, WI) and the Department of Biochemistry at the Medical College of Wisconsin (Milwaukee, WI). CESG develops new methods and technologies to address unique eukaryotic bottlenecks and disseminates its methodologies and experimental results to the scientific community worldwide through: :- Cell-Free Protein Production Workshops :- Plasmids at PSI Materials Repository :- Posters Presented at Scientific Meetings :- Publications in PubMed / PubMed Central :- Sesame (LIMS) Available for Researchers :- Solved Structures in the Protein Data Bank :- Technology Dissemination Reports They have welcomed requests by researchers to solve eukaryotic protein structures, particularly medically relevant proteins, through our Online Structure Request System for Researchers. They have solved many community-nominated targets and deposited information about these targets in public databases and published on our investigations and findings. Sponsors: CESG is supported by NIH / NIGMS Protein Structure Initiative grant numbers U54 GM074901 and P50 GM064598.

Proper citation: CESG (RRID:SCR_008451) Copy   

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http://www.informatics.jax.org

International database for laboratory mouse. Data offered by The Jackson Laboratory includes information on integrated genetic, genomic, and biological data. MGI creates and maintains integrated representation of mouse genetic, genomic, expression, and phenotype data and develops reference data set and consensus data views, synthesizes comparative genomic data between mouse and other mammals, maintains set of links and collaborations with other bioinformatics resources, develops and supports analysis and data submission tools, and provides technical support for database users. Projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, and MouseCyc Project at MGI.

Proper citation: Mouse Genome Informatics (MGI) (RRID:SCR_006460) Copy   

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http://www.jurgott.org/linkage/ListSoftware.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 4th,2023. Listing of computer software for the gene mapping community on the following topics: genetic linkage analysis for human pedigree data, QTL analysis for animal/plant breeding data, genetic marker ordering, genetic association analysis, haplotype construction, pedigree drawing, and population genetics. The inclusion of a program should not be interpreted as an endorsement to that program from us. In the last few years, new technology produces new types of genetic data, and the scope of genetic analyses change dramatically. It is no longer obvious whether a program should be included or excluded from this list. Topics such as next-generation-sequencing (NGS), gene expression, genomics annotation, etc. can all be relevant to a genetic study, yet be specialized topics by themselves. Though programs on variance calling from NSG can be in, those can sequence alignment might be out; programs on eQTL can be in, those on differential expression might be out. This page was created by Dr. Wentian Li, when he was at Columbia University (1995-1996). It was later moved to Rockefeller University (1996-2002), and now takes its new home at North Shore LIJ Research Institute (2002-now). The present copy is maintained by Jurg Ott as a single file. More than 240 programs have been listed by December 2004, more than 350 programs by August 2005, close to 400 programs by December 2006, and close to 480 programs by November 2008, and over 600 programs by October 2012. A version of the searchable database was developed by Zhiliang Hu of Iowa State University, and a recent round of updating was assisted by Wei JIANG of Harbin Medical School. Some earlier software can be downloaded from EBI: ftp://ftp.ebi.ac.uk/pub/software/linkage_and_mapping/ (Linkage and Mapping Software Repository), and http://genamics.com/software/index.htm may contain archived copy of some programs.

Proper citation: Genetic Analysis Software (RRID:SCR_013155) Copy   

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http://rdocdb.nimh.nih.gov

A database that houses human subjects data related to mental health research. Data from 691 subjects are shared in RDoCdb and data from 100,500 subjects are shared in the NIMH Data Archive. Users can plan for data submission, share data, query data, or share their results related to a publication or finding.

Proper citation: RDoCdb (RRID:SCR_013796) Copy   

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http://www.socr.ucla.edu/

A hierarchy of portable online interactive aids for motivating, modernizing probability and statistics applications. The tools and resources include a repository of interactive applets, computational and graphing tools, instructional and course materials. The core SOCR educational and computational components include the following suite of web-based Java applets: * Distributions (interactive graphs and calculators) * Experiments (virtual computer-generated games and processes) * Analyses (collection of common web-accessible tools for statistical data analysis) * Games (interfaces and simulations to real-life processes) * Modeler (tools for distribution, polynomial and spectral model-fitting and simulation) * Graphs, Plots and Charts (comprehensive web-based tools for exploratory data analysis), * Additional Tools (other statistical tools and resources) * SOCR Java-based Statistical Computing Libraries * SOCR Wiki (collaborative Wiki resource) * Educational Materials and Hands-on Activities (varieties of SOCR educational materials), * SOCR Statistical Consulting In addition, SOCR provides a suite of tools for volume-based statistical mapping (http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLine) via command-line execution and via the LONI Pipeline workflows (http://www.nitrc.org/projects/pipeline). Course instructors and teachers will find the SOCR class notes and interactive tools useful for student motivation, concept demonstrations and for enhancing their technology based pedagogical approaches to any study of variation and uncertainty. Students and trainees may find the SOCR class notes, analyses, computational and graphing tools extremely useful in their learning/practicing pursuits. Model developers, software programmers and other engineering, biomedical and applied researchers may find the light-weight plug-in oriented SOCR computational libraries and infrastructure useful in their algorithm designs and research efforts. The three types of SOCR resources are: * Interactive Java applets: these include a number of different applets, simulations, demonstrations, virtual experiments, tools for data visualization and analysis, etc. All applets require a Java-enabled browser (if you see a blank screen, see the SOCR Feedback to find out how to configure your browser). * Instructional Resources: these include data, electronic textbooks, tutorials, etc. * Learning Activities: these include various interactive hands-on activities. * SOCR Video Tutorials (including general and tool-specific screencasts).

Proper citation: Statistics Online Computational Resource (RRID:SCR_003378) Copy   

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