A5059590876- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Bioinformatics and Genomic Networks
- Scientific Computing and Data Management
- Genetics, Bioinformatics, and Biomedical Research
- Genomics and Phylogenetic Studies
- Research Data Management Practices
- Service-Oriented Architecture and Web Services
- Microbial Community Ecology and Physiology
- Microbial Natural Products and Biosynthesis
- Advanced Computational Techniques and Applications
- Advanced Proteomics Techniques and Applications
- Indigenous Cultures and History
- Computational Drug Discovery Methods
- Botanical Research and Chemistry
- Radiomics and Machine Learning in Medical Imaging
- Land Rights and Reforms
- Machine Learning in Bioinformatics
- History and Politics in Latin America
- Genomics and Rare Diseases
- Argentine historical studies
- Intellectual Capital and Performance Analysis
- Lung Cancer Treatments and Mutations
- University-Industry-Government Innovation Models
- Biomedical and Engineering Education
Norwegian University of Science and Technology
2011-2022
Bayer (United States)
2020
Bayer (France)
2020
Bayer (Belgium)
2020
The Kinghorn Cancer Centre
2018
Waikato Hospital
2018
Garvan Institute of Medical Research
2018
Bayer (Germany)
2017
Stanford University
2015
King Abdullah University of Science and Technology
2015
Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture agrifood systems requires quality labeling or annotation in order to be interoperable. As recommended the FAIR principles, data, labels, metadata must use controlled vocabularies ontologies that are popular knowledge domain commonly used community. Despite existence of robust Life Sciences, there is currently no comprehensive full set for across agricultural disciplines. In this paper, we discuss...
Bio-ontologies are key elements of knowledge management in bioinformatics. Rich and rigorous bio-ontologies should represent biological with high fidelity robustness. The richness is a prior condition for diverse efficient reasoning, hence querying hypothesis validation. Rigour allows more consistent maintenance. Modelling such is, however, difficult task bio-ontologists, because the necessary rigour to achieve without extensive training. Analogous design patterns software engineering,...
Abstract Background Life scientists need help in coping with the plethora of fast growing and scattered knowledge resources. Ideally, this should be integrated a form that allows them to pose complex questions address properties biological systems, independently from origin knowledge. Semantic Web technologies prove well suited for integration, production (hypothesis formulation), querying maintenance. Results We implemented semantically resource named BioGateway, comprising entire set OBO...
The application of semantic technologies to the integration biological data and interoperability bioinformatics analysis visualization tools has been common theme a series annual BioHackathons hosted in Japan for past five years. Here we provide review activities outcomes from held 2011 Kyoto 2012 Toyama. In order efficiently implement life sciences, participants formed various sub-groups worked on following topics: Resource Description Framework (RDF) models specific domains, text mining...
During BioHackathon 24 in Fukushima, we organized a WikiBlitz, collaborative effort to integrate biodiversity observations from iNaturalist into the Wikimedia ecosystem. A WikiBlitz is inspired by concept of BioBlitz, where participants document as many species possible within limited time frame, while also contributing structured data Wikidata, Commons, and Wikipedia. In this report, describe methodology outcomes event, including collection 109 their subsequent verification integration...
The Cell Cycle Ontology ( http://www.CellCycleOntology.org ) is an application ontology that automatically captures and integrates detailed knowledge on the cell cycle process. enabled by semantic web technologies, accessible via for browsing, visualizing, advanced querying, computational reasoning. facilitates a analysis of cycle-related molecular network components. Through querying automated reasoning, it may provide new hypotheses to help steer systems biology approach biological building.
Abstract Motivation: Ontologies have become indispensable in the Life Sciences for managing large amounts of knowledge. The use logics ontologies ranges from sound modelling to practical querying that knowledge, thus adding a considerable value. We conceive reasoning on bio-ontologies as semi-automated process three steps: (i) defining logic-based representation language; (ii) building consistent ontology using and (iii) exploiting through querying. Results: Here, we report how implemented...
BioHackathon 2010 was the third in a series of meetings hosted by Database Center for Life Sciences (DBCLS) Tokyo, Japan. The overall goal is to improve quality and accessibility life science research data on Web bringing together representatives from public databases, analytical tool providers, cyber-infrastructure researchers jointly tackle important challenges area silico biological research. theme 'Semantic Web', all attendees gathered with shared producing Semantic their respective...
Abstract As ontologies are developed there is a common need to transform them, especially from those that axiomatically lean rich. Such transformations often require large numbers of axioms be generated affect many different parts the ontology. This paper describes Ontology Pre-Processor Language (OPPL), domain-specific macro language, based in Manchester OWL Syntax, for manipulating written OWL. OPPL instructions can add/remove entities, and (semantics or annotations) to/from entities an...
Abstract Motivation: Many biomedical ontologies use OBO or OWL as knowledge representation language. The rapid increase of such calls for adequate tools to facilitate their use. In particular, there is a pressing need programmatically deal with in many applications, including data integration, text mining, well semantic applications supporting translational research. Results: We present an Application Programming Interface (API) called ONTO-PERL. This API significantly extends the repertoire...
Abstract Background Semantic Web technologies have been developed to overcome the limitations of current and conventional data integration solutions. The is expected link all present on Internet instead linking just documents. One foundations knowledge representation language Resource Description Framework (RDF). Knowledge expressed in RDF typically stored so-called triple stores (also known as stores), from which it can be retrieved with SPARQL, a designed for querying RDF-based models....
The biosciences increasingly face the challenge of integrating a wide variety available data, information and knowledge in order to gain an understanding biological systems. Data integration is supported by diverse series tools, but lack consistent terminology label these data still presents significant hurdles. As consequence, much remains disconnected or worse: becomes misconnected. need address this problem has spawned building large number bio-ontologies. OBOF, RDF OWL are among most...
There is as yet no computer-processable resource to describe treatment end points in cancer, hindering our ability systematically capture and share outcomes data inform better patient care. To address these unmet needs, we have built an ontology, the Cancer Care Treatment Outcome Ontology (CCTOO), organize high-level concepts of with structured knowledge representation facilitate standardized sharing real-world data.End from oncology trials ClinicalTrials.gov were extracted, queried using...
As ontologies are developed there is a common need to transform them, especially from those that axiomatically lean rich. Such transformations often require large numbers of axioms be generated affect many different parts the ontology. This paper describes Ontology Pre-Processor Language (OPPL), domain-specific macro language, based in Manchester OWL Syntax, for manipulating written OWL. OPPL instructions can add/remove entities, and (semantics or annotations) to/from entities an suitable...
<ns3:p>We report on the activities of 2015 edition BioHackathon, an annual event that brings together researchers and developers from around world to develop tools technologies promote reusability biological data. We discuss issues surrounding representation, publication, integration, mining reuse data metadata across a wide range biomedical types relevance for life sciences, including chemistry, genotypes phenotypes, orthology phylogeny, proteomics, genomics, glycomics, metabolomics....
Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture agrifood systems requires quality labelling to be interoperable. As recommended the FAIR principles, data, labels metadata must use controlled vocabularies ontologies that are popular in knowledge domain commonly used community. Despite existence of robust Life Sciences, there is currently no agreed full set for annotation across agricultural disciplines, which may span genetics, environment,...
Biomedical ontologies are key elements for building up the Life Sciences Semantic Web. Reusing and biomedical requires flexible versatile tools to manipulate them efficiently, in particular enriching their axiomatic content. The Ontology Pre Processor Language (OPPL) is an OWL-based language automating changes be performed ontology. OPPL augments ontologists' toolbox by providing a more efficient, less error-prone, mechanism ontology than that obtained manual treatment.We present...
The Semantic Web standards OWL and RDF are often used to represent biomedical information as Linked Data; however, the OWL/RDF syntax, which combines both, was never optimised for querying. By combining two formal paradigms modelling Data,