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http://bioportal.bioontology.org/

Open repository of biomedical ontologies that provides access via Web browsers and Web services to ontologies. It supports ontologies in OBO format, OWL, RDF, Rich Release Format (RRF), Protege frames, and LexGrid XML. Functionality includes the ability to browse, search and visualize ontologies as well as to comment on, and create mappings for ontologies. Any registered user can submit an ontology. The NCBO Annotator and NCBO Resource Index can also be accessed via BioPortal. Additional features: * Add Reviews: rate the ontology according to several criteria and describe your experience using the ontology. * Add Mappings: submit point-to-point mappings or upload bulk mappings created with external tools. Notification of new Mappings is RSS-enabled and Mappings can be browsed via BioPortal and accessed via Web services. * NCBO Annotator: Tool that tags free text with ontology terms. NCBO uses the Annotator to generate ontology annotations, creating an ontology index of these resources accessible via the NCBO Resource Index. The Annotator can be accessed through BioPortal or directly as a Web service. The annotation workflow is based on syntactic concept recognition (using the preferred name and synonyms for terms) and on a set of semantic expansion algorithms that leverage the ontology structure (e.g., is_a relations). * NCBO Resource Index: The NCBO Resource Index is a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to enable users to locate biomedical data linked via ontology terms. A set of annotations is generated automatically, using the NCBO Annotator, and presented in BioPortal. This service uses a concept recognizer (developed by the National Center for Integrative Biomedical Informatics, University of Michigan) to produce a set of annotations and expand them using ontology is_a relations. * Web services: Documentation on all Web services and example code is available at: BioPortal Web services.

Proper citation: BioPortal (RRID:SCR_002713) Copy   

•   Source: SciCrunch Registry

http://clinicalinformatics.stanford.edu/projects/cdw.html

Research and development project at Stanford University to create a standards-based informatics platform supporting clinical and translational research. STRIDE consists of three integrated components: a clinical data warehouse, based on the HL7 Reference Information Model (RIM), containing clinical information on over 1.6 million pediatric and adult patients cared for at Stanford University Medical Center since 1995; an application development framework for building research data management applications on the STRIDE platform and a biospecimen data management system. STRIDE's semantic model uses standardized terminologies, such as SNOMED, RxNorm, ICD and CPT, to represent important biomedical concepts and their relationships. STRIDE receives clinical data for research use via HL7 feeds from both SUMC hospitals: Lucile Packard Children's Hospital and Stanford Hospital and Clinics. This clinical data is used to support a wide variety of translational research services including: * Anonymized Patient Research Cohort Discovery * Electronic Chart Review for Research * IRB-Approved Clinical Data Extraction * Biospecimen Data Management * Multimedia Research * Data Management and Research Registries STRIDE is a highly secure environment utilizing encryption, fine-grained access control, robust auditing and detailed data segregation. Additionally, STRIDE has a robust access control framework with well-defined access granting authorities and access control groups. Consequently STRIDE meets or exceeds the requirements of the HIPAA Privacy and Security regulations. Privacy protection is further enhanced by requiring IRB approval for all research projects using STRIDE clinical data. From a technology and standards perspective, STRIDE is hosted on the Oracle 11g database platform. STRIDE application software provides access to the web services of a three-tier infrastructures using SSL encryption with strong authentication. These programs are cross-platform, self-updating thick-client applications that provides a rich user interface for data entry, retrieval and review as well as image manipulation and annotation. STRIDE makes extensive use of XML technologies for representation of structured meta data, distributed systems technologies using JSON for secure remote communication between client and server, and Swing graphical interface components providing a rich widget-set as well as advanced imaging and graphing capabilities. Users of the STRIDE Research Desktop Client can perform rapid data entry into structured fields, compose complex queries, and interact securely with clinical, research and imaging data.

Proper citation: Stanford Translational Research Integrated Database Environment and Clinical Data Warehouse (RRID:SCR_003453) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/simtkcore

SimTK Core is one of the two packages that together constitute SimTK, the biosimulation toolkit from the Simbios Center. The other major component of SimTK is OpenMM which is packaged separately. This SimTK Core project collects together all the binaries needed for the various SimTK Core subprojects. These include Simbody, Molmodel, Simmath (including Ipopt), Simmatrix, CPodes, SimTKcommon, and Lapack. See the individual projects for descriptions. SimTK brings together in a robust, convenient, open source form the collection of highly-specialized technologies necessary to building successful physics-based simulations of biological structures. These include: strict adherence to an important set of abstractions and guiding principles, robust, high-performance numerical methods, support for developing and sharing physics-based models, and careful software engineering. Accessible High Performance Computing We believe that a primary concern of simulation scientists is performance, that is, speed of computation. We seek to build valid, approximate models using classical physics in order to achieve reasonable run times for our computational studies, so that we can hope to learn something interesting before retirement. In the choice of SimTK technologies, we are focused on achieving the best possible performance on hardware that most researchers actually have. In today''s practice, that means commodity multiprocessors and small clusters. The difference in performance between the best methods and the do-it-yourself techniques most people use can be astoundingeasily an order of magnitude or more. The growing set of SimTK Core libraries seeks to provide the best implementation of the best-known methods for widely used computations such as: Linear algebra, numerical integration and Monte Carlo sampling, multibody (internal coordinate) dynamics, molecular force field evaluation, nonlinear root finding and optimization. All SimTK Core software is in the form of C++ APIs, is thread-safe, and quietly exploits multiple CPUs when they are present. The resulting pre-built binaries are available for download and immediate use. Audience: Biosimulation application programmers interested in including robust, high-performance physics-based simulation in their domain-specific applications.

Proper citation: SimTKCore (RRID:SCR_008268) Copy   

•   Source: SciCrunch Registry

https://bmir-gforge.stanford.edu/gf/project/odie

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. A software toolkit to code document sets with ontologies or to enrich existing ontologies with new concepts from the document set. It contains algorithms for Named Entity Recognition, Co-reference resolution, concept discovery, discourse reasoning and attribute value extraction. The project aimed to develop a toolkit that will provide the following functionality: * Build text processing pipelines that use ontologies to annotate documents. * Enrich ontologies with new concepts that are automatically discovered in documents. * Populate an information model automatically from information extracted from documents. ODIE is open source software released under the LGPL v3.0 License. ODIE is written in Java and uses the Eclipse RCP Framework for the UI. The source code is organized into Eclipse projects.

Proper citation: Ontology Development and Information Extraction (RRID:SCR_003405) Copy   

•   Source: SciCrunch Registry