Developing a kidney and urinary pathway knowledge base

BackgroundChronic renal disease is a global health problem. The identification of suitable biomarkers could facilitate early detection and diagnosis and allow better understanding of the underlying pathology. One of the challenges in meeting this goal is the necessary integration of experimental results from multiple biological levels for further analysis by data mining. Data integration in the life science is still a struggle, and many groups are looking to the benefits promised by the Semantic Web for data integration.ResultsWe present a Semantic Web approach to developing a knowledge base that integrates data from high-throughput experiments on kidney and urine. A specialised KUP ontology is used to tie the various layers together, whilst background knowledge from external databases is incorporated by conversion into RDF. Using SPARQL as a query mechanism, we are able to query for proteins expressed in urine and place these back into the context of genes expressed in regions of the kidney.ConclusionsThe KUPKB gives KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. The Semantic Web technologies we use, together with the background knowledge from the domain’s ontologies, allows both rapid conversion and integration of this knowledge base. The KUPKB is still relatively small, but questions remain about scalability, maintenance and availability of the knowledge itself.AvailabilityThe KUPKB may be accessed via http://www.e-lico.eu/kupkb.

[1]  Ian Horrocks,et al.  FaCT++ Description Logic Reasoner: System Description , 2006, IJCAR.

[2]  Huajun Chen,et al.  The Semantic Web , 2011, Lecture Notes in Computer Science.

[3]  Christopher G. Chute,et al.  BioPortal: ontologies and integrated data resources at the click of a mouse , 2009, Nucleic Acids Res..

[4]  Junjun Zhang,et al.  BioMart Central Portal—unified access to biological data , 2009, Nucleic Acids Res..

[5]  Frank van Harmelen,et al.  Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema , 2002, SEMWEB.

[6]  Carole A. Goble,et al.  An Identity Crisis in the Life Sciences , 2006, IPAW.

[7]  G Stix,et al.  The mice that warred. , 2001, Scientific American.

[8]  Nicole Tourigny,et al.  Bio2RDF: Towards a mashup to build bioinformatics knowledge systems , 2008, J. Biomed. Informatics.

[9]  Mirina Grosz,et al.  World Wide Web Consortium , 2010 .

[10]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[11]  M. Mann,et al.  The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins , 2006, Genome Biology.

[12]  Michel Dumontier,et al.  Proceedings of the 8th International Workshop on OWL: Experiences and Directions , 2011 .

[13]  Carole A. Goble,et al.  State of the nation in data integration for bioinformatics , 2008, J. Biomed. Informatics.

[14]  Kieron O'Hara,et al.  Editorial: Knowledge representation with ontologies: Present challenges-Future possibilities , 2007 .

[15]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[16]  angesichts der Corona-Pandemie,et al.  UPDATE , 1973, The Lancet.

[17]  Jake Yue Chen,et al.  A case study of integrating protein interaction data using semantic web technology , 2007, Int. J. Bioinform. Res. Appl..

[18]  Kurt Rohloff,et al.  An Evaluation of Triple-Store Technologies for Large Data Stores , 2007, OTM Workshops.

[19]  John M. Hancock,et al.  Using ontologies to describe mouse phenotypes , 2004, Genome Biology.

[20]  Kei-Hoi Cheung,et al.  AlzPharm: integration of neurodegeneration data using RDF , 2007, BMC Bioinformatics.

[21]  Amit P. Sheth,et al.  An ontology-driven semantic mashup of gene and biological pathway information: Application to the domain of nicotine dependence , 2008, J. Biomed. Informatics.

[22]  Martin J. O'Connor,et al.  Mapping Master: A Flexible Approach for Mapping Spreadsheets to OWL , 2010, SEMWEB.

[23]  Atanas Kiryakov,et al.  OWLIM - A Pragmatic Semantic Repository for OWL , 2005, WISE Workshops.

[24]  Boris Motik,et al.  Hypertableau Reasoning for Description Logics , 2009, J. Artif. Intell. Res..

[25]  Michael Y. Galperin.  The Molecular Biology Database Collection: 2005 update , 2004, Nucleic Acids Res..

[26]  Abraham Bernstein,et al.  An overview of intelligent data assistants for data analysis , 2010 .

[27]  Robert Stevens,et al.  Using OWL to model biological knowledge , 2007, Int. J. Hum. Comput. Stud..

[28]  Michael Y. Galperin.  The Molecular Biology Database Collection: 2008 update , 2007, Nucleic Acids Res..

[29]  James A. Hendler,et al.  The Semantic Web" in Scientific American , 2001 .

[30]  Anna Zhukova,et al.  Modeling sample variables with an Experimental Factor Ontology , 2010, Bioinform..

[31]  Yarden Katz,et al.  Pellet: A practical OWL-DL reasoner , 2007, J. Web Semant..

[32]  Adrian Paschke,et al.  A journey to Semantic Web query federation in the life sciences , 2009, BMC Bioinformatics.

[33]  Comparison of Triple Stores , 2009 .

[34]  Cynthia L. Smith,et al.  Integrating phenotype ontologies across multiple species , 2010, Genome Biology.

[35]  Jean-Christophe Aude,et al.  A panoramic view of gene expression in the human kidney , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[36]  Allam Appa Rao,et al.  Techniques for integrating ‐omics data , 2009, Bioinformation.

[37]  B Marshall,et al.  Gene Ontology Consortium: The Gene Ontology (GO) database and informatics resource , 2004, Nucleic Acids Res..

[38]  Bijan Parsia,et al.  SPARQL-DL: SPARQL Query for OWL-DL , 2007, OWLED.

[39]  Harald Mischak,et al.  Urine in Clinical Proteomics* , 2008, Molecular & Cellular Proteomics.

[40]  Emmanuel Barillot,et al.  XML, bioinformatics and data integration , 2001, Bioinform..

[41]  Chris T. A. Evelo,et al.  The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services , 2010, BMC Bioinformatics.

[42]  M. Ashburner,et al.  An ontology for cell types , 2005, Genome Biology.

[43]  Bernard De Baets,et al.  BioGateway: a semantic systems biology tool for the life sciences , 2009, BMC Bioinformatics.

[44]  José L. V. Mejino,et al.  A reference ontology for biomedical informatics: the Foundational Model of Anatomy , 2003, J. Biomed. Informatics.

[45]  Matthew Horridge,et al.  Supporting Early Adoption of OWL 1.1 with Protege-OWL and FaCT++ , 2006, OWLED.

[46]  Jessica A. Turner,et al.  Modeling biomedical experimental processes with OBI , 2010, J. Biomed. Semant..

[47]  Gene Ontology Consortium.  The Gene Ontology (GO) database and informatics resource , 2003 .

[48]  L. Stein,et al.  OWL Web Ontology Language - Reference , 2004 .

[49]  José L. V. Mejino,et al.  CARO - The Common Anatomy Reference Ontology , 2008, Anatomy Ontologies for Bioinformatics.

[50]  Markus Krötzsch,et al.  SPARQL beyond Subgraph Matching , 2010, SEMWEB.

[51]  Ian Horrocks,et al.  OWL Web Ontology Language Reference-W3C Recommen-dation , 2004 .

[52]  Carole A. Goble,et al.  BioCatalogue: a universal catalogue of web services for the life sciences , 2010, Nucleic Acids Res..

[53]  A. Bello,et al.  Chronic kidney disease: the global challenge , 2005, The Lancet.

[54]  Ian Horrocks,et al.  The GRAIL concept modelling language for medical terminology , 1997, Artif. Intell. Medicine.

[55]  Alan Ruttenberg,et al.  Overcoming the ontology enrichment bottleneck with Quick Term Templates , 2011, Appl. Ontology.

[56]  M. Ashburner,et al.  The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration , 2007, Nature Biotechnology.

[57]  A. Rector,et al.  Relations in biomedical ontologies , 2005, Genome Biology.

[58]  Peter Buneman,et al.  Challenges in Integrating Biological Data Sources , 1995, J. Comput. Biol..

[59]  Mary E. Mangan,et al.  The Adult Mouse Anatomical Dictionary: a tool for annotating and integrating data , 2005, Genome Biology.

[60]  Alan Ruttenberg,et al.  Life sciences on the Semantic Web: the Neurocommons and beyond , 2009, Briefings Bioinform..

[61]  Martin Kuiper,et al.  Biological knowledge management: the emerging role of the Semantic Web technologies , 2009, Briefings Bioinform..

[62]  Ralf Hofestädt,et al.  BioDWH: A Data Warehouse Kit for Life Science Data Integration , 2008, J. Integr. Bioinform..

[63]  W. Alex Gray,et al.  Bioinformatics Data Source Integration Based on Semantic Relationships Across Species , 2006, VDMB.

[64]  T. Venkatesh,et al.  Integromics: challenges in data integration , 2002, Genome Biology.

[65]  Michael Hsing and Artem Cherkasov.  Integration of Biological Data with Semantic Networks , 2006 .

[66]  Martin Norling,et al.  Comprehensive human urine standards for comparability and standardization in clinical proteome analysis , 2010, Proteomics. Clinical applications.

[67]  Kelli Montgomery,et al.  Gene expression in the normal adult human kidney assessed by complementary DNA microarray. , 2003, Molecular biology of the cell.