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http://www.elsevier.com/online-tools/pathway-studio/biological-database
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. MedScan is a fast and flexible biomedical information extraction technology. It uses dictionaries to identify individual biomedical terms (proteins, cellular processes, small molecules, diseases, etc) referred to in literature articles, and applies advanced natural language processing techniques to detect the relationships within the article and extract these terms and the relationships; the overall process of detection, identification, extraction and assembling, is termed Information Harvesting. Information extracted by MedScan represents the multiple aspects of protein function, including protein modification, cellular localization, protein-protein interactions, gene expression regulation, molecular transport and synthesis, as well as association with diseases, and regulation of various cellular processes. This scope can be broadened by modifying information extraction rules and the dictionaries. Dictionaries can be assembled on any topic or area that is represented in the literature you wish to harvest. High-throughput data generation methodologies like microarray gene expression require new approaches for gathering information for data analysis. For the best results, computational approaches used for high-throughput data analysis require that biological information from the literature be a coherent and integrated part of the analysis software itself. Pathway Studio meets this challenge through its MedScan Technology and underlying ResNet database. All editions of Pathway Studio contain MedScan Technology to harvest information from the literature and to save this information in the Pathway Studio ResNet database ready for data analysis. MedScan is more than a web search engine. Indeed, the output of a Google search can be channeled into MedScan for example. Web searches, like Google, are excellent at finding items as a result of a query. A quick look at the output list usually locates the item for which you are looking. This approach however, is not well suited for information and knowledge gathering. Also, once information is gathered, where do you put it for later computational use? MedScan meets this challenge for the area of biomedical literature and biomedical online information. PubMed meets the needs for a central repository of biomedical literature. Researchers can go to PubMed and search for any topic and articles of interest, much like a web type of search. However, just like a web type of search, PubMed also provides a list of all the hits with a link to the articles. If a single article, or even just a few, are sought, this search approach is useful. Alternatively, MedScan will list all the articles of interest but additionally scans the text for relationships, highlights these relationships in the articles and then lists these relationships and the biological molecules and processes involved in the relationships in separate tables. The tables of relationships can be viewed graphically in Pathway Studio and can be saved into the ResNet database for use in experimental data analysis.
Proper citation: MedScan (RRID:SCR_003314) Copy
Protege is a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies. At its core, Protege implements a rich set of knowledge-modeling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protege can be customized to provide domain-friendly support for creating knowledge models and entering data. Further, Protege can be extended by way of a plug-in architecture and a Java-based Application Programming Interface (API) for building knowledge-based tools and applications. An ontology describes the concepts and relationships that are important in a particular domain, providing a vocabulary for that domain as well as a computerized specification of the meaning of terms used in the vocabulary. Ontologies range from taxonomies and classifications, database schemas, to fully axiomatized theories. In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services. The Protege platform supports two main ways of modeling ontologies: * The Protege-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties. * The Protege-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's Web Ontology Language (OWL). An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms (see the OWL Web Ontology Language Guide). Protege is based on Java, is extensible, and provides a plug-and-play environment that makes it a flexible base for rapid prototyping and application development.
Proper citation: Protege (RRID:SCR_003299) Copy
Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.
Proper citation: Reactome (RRID:SCR_003485) Copy
http://www.isi.edu/integration/karma/
An information integration software tool that enables users to integrate data from a variety of data sources including databases, spreadsheets, delimited text files, XML, JSON, KML and Web APIs. Users integrate information by modeling it according to an ontology of their choice using a graphical user interface that automates much of the process. Karma learns to recognize the mapping of data to ontology classes and then uses the ontology to propose a model that ties together these classes. Users then interact with the system to adjust the automatically generated model. During this process, users can transform the data as needed to normalize data expressed in different formats and to restructure it. Once the model is complete, users can publish the integrated data as RDF or store it in a database.
Proper citation: Karma (RRID:SCR_003732) Copy
SchistoDB is a genomic database for the parasitic organism Schistosoma mansoni, one of the major causative agents of schistosomiasis worldwide. It currently incorporates sequences and annotation for S. mansoni in a single user-friendly database. Several genomic scale analyses are available as well as ESTs, oligonucleotides, metabolic pathways and drugs. Make your data available: If you''d like to have your updates and/or datasets integrated in SchistoDB, drop us an email.
Proper citation: Schistosoma mansoni Database (RRID:SCR_004341) Copy
http://nematode.lab.nig.ac.jp/
Expression pattern map of the 100Mb genome of the nematode Caenorhabditis elegans through EST analysis and systematic whole mount in situ hybridization. NEXTDB is the database to integrate all information from their expression pattern project and to make the data available to the scientific community. Information available in the current version is as follows: * Map: Visual expression of the relationships among the cosmids, predicted genes and the cDNA clones. * Image: In situ hybridization images that are arranged by their developmental stages. * Sequence: Tag sequences of the cDNA clones are available. * Homology: Results of BLASTX search are available. Users of the data presented on our web pages should not publish the information without our permission and appropriate acknowledgment. Methods are available for: * In situ hybridization on whole mount embryos of C.elegans * Protocols for large scale in situ hybridization on C.elegans larvae
Proper citation: NEXTDB (RRID:SCR_004480) Copy
Public database of information about all clinical trials involving humans, this global initiative provides a single point of access to information about ongoing and completed clinical trials. It contains the trial registration data sets made available by data providers around the world meeting criteria for content and quality control. It also aims to: * To improve the comprehensiveness, completeness and accuracy of registered clinical trial data * To communicate and raise awareness of the need to register clinical trials * To ensure the accessibility of registered data * To build capacity for clinical trial registration * To encourage the utilization of registered data * To ensure the sustainability of the ICTRP The mission of the WHO International Clinical Trials Registry Platform is to ensure that a complete view of research is accessible to all those involved in health care decision making. This will improve research transparency and will ultimately strengthen the validity and value of the scientific evidence base. The registration of all interventional trials is a scientific, ethical and moral responsibility. The ICTRP: * Publishes the ICTRP Search Portal * Supports the WHO Registry Network * Supports countries and regions wanting to establish WHO-compliant clinical trial registries or policies on trial registration.
Proper citation: WHO International Clinical Trials Registry Platform (RRID:SCR_004475) Copy
A dynamic archive of information on digital morphology and high-resolution X-ray computed tomography of biological specimens serving imagery for more than 750 specimens contributed by almost 150 collaborating researchers from the world''s premiere natural history museums and universities. Browse through the site and see spectacular imagery and animations and details on the morphology of many representatives of the Earth''s biota. Digital Morphology, part of the National Science Foundation Digital Libraries Initiative, develops and serves unique 2D and 3D visualizations of the internal and external structure of living and extinct vertebrates, and a growing number of ''invertebrates.'' The Digital Morphology library contains nearly a terabyte of imagery of natural history specimens that are important to education and central to ongoing cutting-edge research efforts. Digital Morphology visualizations are now in use in classrooms and research labs around the world and can be seen in a growing number of museum exhibition halls. The Digital Morphology site currently presents: * QuickTime animations of complete stacks of serial CT sections * Animated 3D volumetric movies of complete specimens * Stereolithography (STL) files of 3D objects that can be viewed interactively and rapidly prototyped into scalable physical 3D objects that can be handled and studied as if they were the original specimens * Informative introductions to the scanned organisms, often written by world authorities * Pertinent bibliographic information on each specimen * Useful links * A course resource for our ''Digital Methods for Paleontology'' course, in which students learn how to generate all of the types of imagery displayed on the Digital Morphology site
Proper citation: DigiMorph (RRID:SCR_004416) Copy
Consortium conducting meta-analyses of genome-wide genetic data for psychiatric disease. Focused on autism, attention-deficit hyperactivity disorder, bipolar disorder, major depressive disorder, schizophrenia, anorexia nervosa (AN), Tourette syndrome (TS), and obsessive-compulsive disorder (OCD). Used to investigate common single nucleotide polymorphisms (SNPs) genotyped on commercial arrays, structural variation (copy number variation) and uncommon or rare genetic variation. To participate you are asked to upload data from your study to central computer used by this consortium. Genetic Cluster Computer serves as data warehouse and analytical platform for this study . When data from your study have been incorporated, account will be provided on central server and access to all GWAS genotypes, phenotypes, and meta-analytic results relevant to deposited data and participation aims. NHGRI GWAS Catalog contains updated information about all GWAS in biomedicine, and is usually excellent starting point to find comprehensive list of studies. Files can be obtained by any PGC member for any disease to which they contributed data. These files can also be obtained by application to NIMH Genetics Repository. Individual-level genotype and phenotype data requires application, material transfer agreement, and informed consent consideration. Some datasets are also in controlled-access dbGaP and Wellcome Trust Case-Control Consortium repositories. PGC members can also receive back cleaned and imputed data and results for samples they contributed to PGC analyses.
Proper citation: Psychiatric Genomics Consortium (RRID:SCR_004495) Copy
http://www.fishbase.org/home.htm
A global species database and encyclopedia of over 32,800 species and subspecies of fishes that is searchable by common name, genus, species, geography, family, ecosystem, references literature, tools, etc. It links to other, related databases such as the Catalog of Fishes, GenBack, and LarvalBase. It is associated with a partner journal, Acta Ichthyologica et Piscatoria. It is available in English, Greek, Spanish, Portuguese, French, Dutch, Italian, and German. Photo and video submissions are welcome. FishBase 2004 is also available on DVD or CD-ROMs with full information on 28,500 species. It comes together with the FishBase 2000 book and can be ordered for 95 US$ including air-mail.
Proper citation: FishBase (RRID:SCR_004376) Copy
https://www.bannerhealth.com/research/locations/sun-health-institute/programs/body-donation
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. An autopsy-based, research-devoted brain bank, biobank and biospecimen bank that derives its human donors from the Arizona Study of Aging and Neurodegenerative Disease (AZSAND), a longitudinal clinicopathological study of the health and diseases of elderly volunteers living in Maricopa county and metropolitan Phoenix, Arizona. Their function is studied during life and their organs and tissue after death. To date, they have concentrated their studies on Alzheimer's disease, Parkinson's disease, heart disease and cancer. They share the banked tissue, biomaterials and biospecimens with qualified researchers worldwide. Registrants with suitable scientific credentials will be allowed access to a database of available tissue linked to relevant clinical information, and will allow tissue requests to be initiated., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Brain and Body Donation Program (RRID:SCR_004822) Copy
An interactive, visual database containing more than 350 small molecule pathways found in humans. More than 2/3 of these pathways (>280) are not found in any other pathway database. SMPDB is designed specifically to support pathway elucidation and pathway discovery in metabolomics, transcriptomics, proteomics and systems biology. It is able to do so, in part, by providing exquisitely detailed, fully searchable, hyperlinked diagrams of human metabolic pathways, metabolic disease pathways, metabolite signaling pathways and drug-action pathways. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Each small molecule is hyperlinked to detailed descriptions contained in the HMDB or DrugBank and each protein or enzyme complex is hyperlinked to UniProt. All SMPDB pathways are accompanied with detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram. The database is easily browsed and supports full text, sequence and chemical structure searching. Users may query SMPDB with lists of metabolite names, drug names, genes / protein names, SwissProt IDs, GenBank IDs, Affymetrix IDs or Agilent microarray IDs. These queries will produce lists of matching pathways and highlight the matching molecules on each of the pathway diagrams. Gene, metabolite and protein concentration data can also be visualized through SMPDB''s mapping interface. All of SMPDB''s images, image maps, descriptions and tables are downloadable.
Proper citation: Small Molecule Pathway Database (RRID:SCR_004844) Copy
http://optn.transplant.hrsa.gov/
The only national patient waiting list and an online database system, called UNet, that links all of the professionals involved in the donation and transplantation system for the collection, storage, analysis, and publication of all OPTN data pertaining to the patient waiting list, organ matching, and transplants. The system contains data regarding every organ donation and transplant event occurring in the U.S. since October 1, 1987. UNet is a fail-safe, 24/7, secure Internet-based transplant information database created to enable the nation''''s organ transplant institutions to: * register patients for transplants * match donated organs to waiting patients * manage the time-sensitive, life-critical data of all patients, before and after their transplants Data reports are available by type: National Data, Regional Data, State Data, Center Data, Build Advanced Report, and Annual Report Data. UNet is being used right now by all of the nation''''s organ transplant programs, organ procurement organizations, and histocompatibility (tissue typing) laboratories working cooperatively to efficiently share a limited number of donated organs among thousands of patients.
Proper citation: Organ Procurement and Transplantation Network (RRID:SCR_004883) Copy
Common repository for diverse human microbiome datsets and minimum reporting standards for Common Fund Human Microbiome Project.
Proper citation: HMP Data Analysis and Coordination Center (RRID:SCR_004919) Copy
Database documenting mycological nomenclatural novelties (new names and combinations) and associated data, for example descriptions and illustrations. The nomenclatural novelties will each be allocated a unique MycoBank number that can be cited in the publication where the nomenclatural novelty is introduced. These numbers will also be used by the nomenclatural database Index Fungorum, with which MycoBank is associated and will also serve as Life Science Identifiers (LSIDs). Nomenclatural experts will be available to check the validity, legitimacy and linguistic correctness of the proposed names in order to avoid nomenclatural errors; however, no censorship whatsoever, (nomenclatural or taxonomic) will be exerted by MycoBank. Deposited names will remain -when desired- strictly confidential until after publication, and will then be accessible through MycoBank, Index Fungorum, GBIF and other international biodiversity initiatives, where they will further be linked to other databases to realize a species bank that eventually will link all databases of life. MycoBank will (when applicable) provide onward links to other databases containing, for example, living cultures, DNA data, reference specimens and pleomorphic names linked to the same holomorph. Authors intending to publish nomenclatural novelties are encouraged to contribute to this new initiative. For the moment 2 search engines are available from the MycoBank website. The first one permits to search for fungal names (at any rank level), the authority or the MycoBank unique number. The second is dedicated to bibliographic queries related to fungal name''''s publications. MycoBank users willing to deposit their data will have to register so that they willbe able to contact the depositor for specific information (e.g. MycoBank number, possible points of attention regarding the name, actual publication, etc), and to avoid fake entries.
Proper citation: MycoBank (RRID:SCR_004950) Copy
Open platform for analyzing and sharing neuroimaging data from human brain imaging research studies. Brain Imaging Data Structure ( BIDS) compliant database. Formerly known as OpenfMRI. Data archives to hold magnetic resonance imaging data. Platform for sharing MRI, MEG, EEG, iEEG, and ECoG data.
Proper citation: OpenNeuro (RRID:SCR_005031) Copy
http://glioblastoma.alleninstitute.org/
Platform for exploring the anatomic and genetic basis of glioblastoma at the cellular and molecular levels that includes two interactive databases linked together by de-identified tumor specimen numbers to facilitate comparisons across data modalities: * The open public image database, here, providing in situ hybridization data mapping gene expression across the anatomic structures inherent in glioblastoma, as well as associated histological data suitable for neuropathological examination * A companion database (Ivy GAP Clinical and Genomic Database) offering detailed clinical, genomic, and expression array data sets that are designed to elucidate the pathways involved in glioblastoma development and progression. This database requires registration for access. The hope is that researchers all over the world will mine these data and identify trends, correlations, and interesting leads for further studies with significant translational and clinical outcomes. The Ivy Glioblastoma Atlas Project is a collaborative partnership between the Ben and Catherine Ivy Foundation, the Allen Institute for Brain Science and the Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment.
Proper citation: Ivy Glioblastoma Atlas Project (RRID:SCR_005044) Copy
GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.
Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy
http://bejerano.stanford.edu/prism/public/html/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: PRISM (Stanford database) (RRID:SCR_005375) Copy
http://fcon_1000.projects.nitrc.org/
Collection of resting state fMRI (R-fMRI) datasets from sites around world. It demonstrates open sharing of R-fMRI data and aims to emphasize aggregation and sharing of well-phenotyped datasets.
Proper citation: 1000 Functional Connectomes Project (RRID:SCR_005361) Copy
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