Guidelines for managing data and processes in bone and cartilage tissue engineering

BackgroundIn the last decades, a wide number of researchers/clinicians involved in tissue engineering field published several works about the possibility to induce a tissue regeneration guided by the use of biomaterials. To this aim, different scaffolds have been proposed, and their effectiveness tested through in vitro and/or in vivo experiments. In this context, integration and meta-analysis approaches are gaining importance for analyses and reuse of data as, for example, those concerning the bone and cartilage biomarkers, the biomolecular factors intervening in cell differentiation and growth, the morphology and the biomechanical performance of a neo-formed tissue, and, in general, the scaffolds' ability to promote tissue regeneration. Therefore standards and ontologies are becoming crucial, to provide a unifying knowledge framework for annotating data and supporting the semantic integration and the unambiguous interpretation of novel experimental results.ResultsIn this paper a conceptual framework has been designed for bone/cartilage tissue engineering domain, by now completely lacking standardized methods. A set of guidelines has been provided, defining the minimum information set necessary for describing an experimental study involved in bone and cartilage regenerative medicine field. In addition, a Bone/Cartilage Tissue Engineering Ontology (BCTEO) has been developed to provide a representation of the domain's concepts, specifically oriented to cells, and chemical composition, morphology, physical characterization of biomaterials involved in bone/cartilage tissue engineering research.ConclusionsConsidering that tissue engineering is a discipline that traverses different semantic fields and employs many data types, the proposed instruments represent a first attempt to standardize the domain knowledge and can provide a suitable means to integrate data across the field.

[1]  Gary D Bader,et al.  BMC Biology BioMed Central , 2007 .

[2]  Nicolas Le Novère,et al.  Identifiers.org and MIRIAM Registry: community resources to provide persistent identification , 2011, Nucleic Acids Res..

[3]  Ling Liu,et al.  Encyclopedia of Database Systems , 2009, Encyclopedia of Database Systems.

[4]  R M Levenson,et al.  Quantification of immunohistochemistry—issues concerning methods, utility and semiquantitative assessment II , 2006, Histopathology.

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

[6]  James A. Hendler,et al.  The National Cancer Institute's Thésaurus and Ontology , 2003, J. Web Semant..

[7]  Grace I. Paterson,et al.  Systematized nomenclature of medicine clinical terms (SNOMED CT) to represent computed tomography procedures , 2011, Comput. Methods Programs Biomed..

[8]  S M Hubbard,et al.  The Physician Data Query (PDQ) cancer information system. , 1986, Journal of cancer education : the official journal of the American Association for Cancer Education.

[9]  Zhiyong Lu,et al.  Database resources of the National Center for Biotechnology Information , 2010, Nucleic Acids Res..

[10]  Bjoern Peters Ontology for Biomedical Investigations , 2009 .

[11]  Jessica A. Turner,et al.  The Ontology for Biomedical Investigations , 2016, PloS one.

[12]  Nathan A. Baker,et al.  NanoParticle Ontology for cancer nanotechnology research , 2011, J. Biomed. Informatics.

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

[14]  Jane Hunter,et al.  The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain , 2011, BMC Bioinformatics.

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

[16]  Alan Ruttenberg,et al.  Ontobee: A Linked Data Server and Browser for Ontology Terms , 2011, ICBO.

[17]  Christian Gilissen,et al.  High density gene expression microarrays and gene ontology analysis for identifying processes in implanted tissue engineering constructs. , 2010, Biomaterials.

[18]  Peter Woollard,et al.  The minimum information required for reporting a molecular interaction experiment (MIMIx) , 2007, Nature Biotechnology.

[19]  C E Lipscomb,et al.  Medical Subject Headings (MeSH). , 2000, Bulletin of the Medical Library Association.

[20]  Toshihisa Takagi,et al.  Pacific Symposium on Biocomputing 11:152-163(2006) EVENT ONTOLOGY: A PATHWAY-CENTRIC ONTOLOGY FOR BIOLOGICAL PROCESSES , 2022 .

[21]  Gianluca De Leo,et al.  Fluorescence microscopy imaging of bone for automated histomorphometry. , 2002, Tissue engineering.

[22]  Francesco Beltrame,et al.  A simple non invasive computerized method for the assessment of bone repair within osteoconductive porous bioceramic grafts. , 2005, Biotechnology and bioengineering.

[23]  B. Hammond Ontology , 2004, Lawrence Booth’s Book of Visions.

[24]  Rolf Apweiler,et al.  The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries , 2006, BMC Bioinformatics.

[25]  Mara Riminucci,et al.  Bone Marrow Stromal Stem Cells: Nature, Biology, and Potential Applications , 2001, Stem cells.

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

[27]  J. Blake Bio-ontologies—fast and furious , 2004, Nature Biotechnology.

[28]  Melinda R. Dwinell,et al.  Three Ontologies to Define Phenotype Measurement Data , 2012, Front. Gene..

[29]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[30]  Larry V McIntire,et al.  Automated Selection of DAB-labeled Tissue for Immunohistochemical Quantification , 2003, The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society.

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

[32]  Christoph Steinbeck,et al.  Chemical Entities of Biological Interest: an update , 2009, Nucleic Acids Res..

[33]  Antje Chang,et al.  The BRENDA Tissue Ontology (BTO): the first all-integrating ontology of all organisms for enzyme sources , 2010, Nucleic Acids Res..

[34]  Lennart Martens,et al.  The minimum information about a proteomics experiment (MIAPE) , 2007, Nature Biotechnology.

[35]  Carlo Torniai,et al.  eagle-i: An Ontology-Driven Framework For Biomedical Resource Curation And Discovery , 2010 .

[36]  S. Scaglione,et al.  Regulatory influence of scaffolds on cell behavior: how cells decode biomaterials. , 2011, Current pharmaceutical biotechnology.

[37]  Ivan Merelli,et al.  Bioinformatics approach for data management about bone cells grown on substitute materials , 2012 .

[38]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[39]  C. Sander,et al.  The HUPO PSI's Molecular Interaction format—a community standard for the representation of protein interaction data , 2004, Nature Biotechnology.

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

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

[42]  Gregory D. Schuler,et al.  Database resources of the National Center for Biotechnology Information: update , 2004, Nucleic acids research.

[43]  Chris F. Taylor,et al.  The MGED Ontology: a resource for semantics-based description of microarray experiments , 2006, Bioinform..