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BiOS is a response to inequities in food security, nutrition, health, natural resource management and energy. Our goal is to democratise problem solving to enable diverse solutions through decentralised innovation. Open Source We promote an innovation paradigm that focuses on a distinction between the tools of innovation and the products. We promote licenses that couple rights with responsibilities to foster efficient development, improvement, sharing and use of technology. Open Science We create and share new biological enabling technologies and platforms that can be used to deliver innovations. We develop new licensing and distributive collaboration mechanisms that have resonance with the open source software movement, but are tailored for biological innovation. Open Society We enhance the transparency, accessibility and capability to use all the tools of science, whether patented, open access or public domain.

The Bio2RDF project is a tool to convert bioinformatics data and knowledge bases to RDF format. It is a kind of generalized rdfizer for bioinformatics applications, and it is a place for the semantic web life science community to develop and grow.

Semantic web atlas of postgenomic knowledge about human and mouse

Welcome to the biology portal. Biology, from the Greek words bios (life) and the suffix -ology, meaning study of, is a branch of science. It is concerned with the characteristics and behaviors of organisms, how species and individuals come into existence, and the interactions they have with each other and with their environment. Biology encompasses a broad spectrum of academic fields that are often viewed as independent disciplines. Together, they study life over a wide range of scales.

BioForge was created to encourage online collaborations between diverse research groups under BiOS-based licensing schemes. CAMBIA believes that enabling technologies in the life sciences need to remain available to anyone to improve or use in new innovations, both commercial and non-commercial.

Bio-Pedia is an openfree bioinfomation encyclopedia. You can freely add words and modify them anytime. We are making a biology specific openfree encyclopedia for the world.

Cyberinfrastructure for Phylogenetic Research (CIPRES) project is an open collaboration funded by the National Science Foundation. The group is led by Tandy Warnow and involves researchers (biologists, computer scientists, statisticians, and mathematicians) at sixteen institutions. The goal of the CIPRES project is to enable large-scale phylogenetic reconstructions on a scale that will enable analyses of huge data sets containing hundreds of thousands of bio molecular sequences. To achieve this goal we have brought together a group of researchers involved in phylogeny estimation, statistics, and computer science to create new solutions for the difficult computational problems that arise in inferring evolutionary relationships.

See also http://www.cs.utexas.edu/~tandy/ SATe bio tree software and data

The National Center for Biomedical Ontology is a consortium of leading biologists, clinicians, informaticians, and ontologists who develop innovative technology and methods allowing scientists to create, disseminate, and manage biomedical information and knowledge in machine-processable form. Our visionis that all biomedical knowledge and data are disseminated on the Internet using principled ontologies, such that they are semantically interoperable and useful for improving biomedical science and clinical care. Our resources include the Open Biomedical Ontologies (OBO) library, the Open Biomedical Data (OBD) repositories, and tools for accessing and using this information in research. The Center collaborates with biomedical researchers conducting Driving Biological Projects to enable outside research and stimulate technology development in the Center. The Center undertakes outreach and educational activities (Biomedical Informatics Program) to train future researchers to use biomedical ontologies and related tools with the goal of enhancing scientific discovery.

The Biomedical Grid Terminology (BiomedGT) is an open, collaboratively developed terminology for translational research. BiomedGT builds on the strengths of the NCI Thesaurus, including concept orientation, description logic, and public accessibility. While the current terminology has been seeded with NCI Thesaurus content, it is being restructured to facilitate open content development. The goal is to evolve BiomedGT into a set of federated sub-terminologies, with content maintained by experts in the relevant research communities.

The OBO Foundry is a collaborative experiment involving developers of science-based ontologies who are establishing a set of principles for ontology development with the goal of creating a suite of orthogonal interoperable reference ontologies in the biomedical domain. The groups developing ontologies who have expressed an interest in this goal are listed below, followed by other relevant efforts in this domain.

The prototype we describe is a biomedical knowledge base, constructed for a demonstration at Banff WWW2007 , that integrates 15 distinct data sources using currently available Semantic Web technologies such as the W3C standard Web Ontology Language [OWL] and Resource Description Framework [RDF]. This report outlines which resources were integrated, how the knowledge base was constructed using free and open source triple store technology, how it can be queried using the W3C Recommended RDF query language SPARQL [SPARQL], and what resources and inferences are involved in answering complex queries. While the utility of the knowledge base is illustrated by identifying a set of genes involved in Alzheimer's Disease, the approach described here can be applied to any use case that integrates data from multiple domains.

This is the homepage for an ongoing research and development project named PATIKA - Pathway Analysis Tools for Integration and Knowledge Acquisition. Within this project so far, among others, an ontology has been defined; a pathway database (which integrates and interfaces with several public pathway databases) has been constructed; and some software tools have been developed for effective integration, querying, analysis, and manipulation of pathway data.

This is a sub-project of the BioMoby project. It aims to develop tools in Java in order: * to access BioMoby registries, allowing all features provided by such registries, including but not limited to registering and deregistering of the BioMoby services and their parts, discovering them, and understanding their data in various formats (such as RDF), * to create Java implementations of BioMoby services, especially to help service providers with creating BioMoby data containers (input and output data) without exposing providers to the complexity of the XML required and produced by BioMoby services, and finally

NCBO Seminar Series talks occur via the Web and teleconference at 10:00AM, Pacific time, the 1st and 3rd Wednesday of every month. This series aims to showcase new projects, technologies and ideas in biomedical ontology by featuring the work of a different collaborator each session. It is open to anyone interested, regardless of location or affiliation.

Primary Objectives * Build a demo that spans from bench to bedside using RDF and OWL. * Explore the effectiveness of current tools. * Document our finding to help accelerate adoption of the Semantic Web.

# The primary intention of creating aTags is not the categorization of the document, but the representation of the key facts inside the document. Key facts in the biomedical domain might be, for example, "Protein A interacts with protein B" or "Overexpression of protein A in tissue B is the cause of disease C". # An aTag is comprised of a set of associated entities. The size of the set is arbitrary, but will typically lie between 2 and 5 entities. For example, the fact "Protein A binds to protein B" can be represented with an aTag comprising of the three entities "Protein A", "Molecular interaction" and "Protein B". Similarly, the fact "Overexpression of protein A in tissue B is the cause of disease C" can be represented with an aTag comprising of the four entities "Overexpression", "Protein A", "Tissue B" and "Disease C". # Each document or database entry can be described with an arbitrary number of such aTags. Each aTag can be associated with the relevant portions of text or data in a fine granularity. # The entities in an aTag are not simple strings, but resources that are part of ontologies and RDF/OWL-enabled databases. For example, "Protein A" and "Protein B" are resources that are defined in the UniProt database, whereas "Molecular Interaction" is a class in the branch of biological processes of the Gene Ontology. They are identified with their URIs.