Literature DB >> 18472304

Bio2RDF: towards a mashup to build bioinformatics knowledge systems.

François Belleau1, Marc-Alexandre Nolin, Nicole Tourigny, Philippe Rigault, Jean Morissette.   

Abstract

Presently, there are numerous bioinformatics databases available on different websites. Although RDF was proposed as a standard format for the web, these databases are still available in various formats. With the increasing popularity of the semantic web technologies and the ever growing number of databases in bioinformatics, there is a pressing need to develop mashup systems to help the process of bioinformatics knowledge integration. Bio2RDF is such a system, built from rdfizer programs written in JSP, the Sesame open source triplestore technology and an OWL ontology. With Bio2RDF, documents from public bioinformatics databases such as Kegg, PDB, MGI, HGNC and several of NCBI's databases can now be made available in RDF format through a unique URL in the form of http://bio2rdf.org/namespace:id. The Bio2RDF project has successfully applied the semantic web technology to publicly available databases by creating a knowledge space of RDF documents linked together with normalized URIs and sharing a common ontology. Bio2RDF is based on a three-step approach to build mashups of bioinformatics data. The present article details this new approach and illustrates the building of a mashup used to explore the implication of four transcription factor genes in Parkinson's disease. The Bio2RDF repository can be queried at http://bio2rdf.org.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18472304     DOI: 10.1016/j.jbi.2008.03.004

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  187 in total

1.  At the intersection of public-health informatics and bioinformatics: using advanced Web technologies for phylogeography.

Authors:  Matthew Scotch; Changjiang Mei; Cynthia Brandt; Indra Neil Sarkar; Kei Cheung
Journal:  Epidemiology       Date:  2010-11       Impact factor: 4.822

2.  Mining relational paths in integrated biomedical data.

Authors:  Bing He; Jie Tang; Ying Ding; Huijun Wang; Yuyin Sun; Jae Hong Shin; Bin Chen; Ganesh Moorthy; Judy Qiu; Pankaj Desai; David J Wild
Journal:  PLoS One       Date:  2011-12-06       Impact factor: 3.240

3.  GT2RDF: Semantic Representation of Genetic Testing Data.

Authors:  Anamika Paul Rupa; Sweta Singh; Qian Zhu
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

4.  A semantic web framework to integrate cancer omics data with biological knowledge.

Authors:  Matthew E Holford; James P McCusker; Kei-Hoi Cheung; Michael Krauthammer
Journal:  BMC Bioinformatics       Date:  2012-01-25       Impact factor: 3.169

Review 5.  Using views of Systems Biology Cloud: application for model building.

Authors:  Oliver Ruebenacker; Michael Blinov
Journal:  Theory Biosci       Date:  2010-08-21       Impact factor: 1.919

6.  S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.

Authors:  Helena F Deus; Miriã C Correa; Romesh Stanislaus; Maria Miragaia; Wolfgang Maass; Hermínia de Lencastre; Ronan Fox; Jonas S Almeida
Journal:  BMC Bioinformatics       Date:  2011-07-14       Impact factor: 3.169

7.  Semantic Web repositories for genomics data using the eXframe platform.

Authors:  Emily Merrill; Stéphane Corlosquet; Paolo Ciccarese; Tim Clark; Sudeshna Das
Journal:  J Biomed Semantics       Date:  2014-06-03

8.  Toward a complete dataset of drug-drug interaction information from publicly available sources.

Authors:  Serkan Ayvaz; John Horn; Oktie Hassanzadeh; Qian Zhu; Johann Stan; Nicholas P Tatonetti; Santiago Vilar; Mathias Brochhausen; Matthias Samwald; Majid Rastegar-Mojarad; Michel Dumontier; Richard D Boyce
Journal:  J Biomed Inform       Date:  2015-04-24       Impact factor: 6.317

Review 9.  Integrative approaches for predicting in vivo effects of chemicals from their structural descriptors and the results of short-term biological assays.

Authors:  Yen Sia Low; Alexander Yeugenyevich Sedykh; Ivan Rusyn; Alexander Tropsha
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

10.  BioGPS and GXD: mouse gene expression data-the benefits and challenges of data integration.

Authors:  Martin Ringwald; Chunlei Wu; Andrew I Su
Journal:  Mamm Genome       Date:  2012-07-31       Impact factor: 2.957

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.