http://precedings.nature.com/users/9231d6549cae1b30f87399e05ba6cc5b/ Documents posted by Barry Smith Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3960.1 Definitive diagnosis of malaria requires the demonstration through laboratory tests of the presence within the patient of malaria parasites or their components. Since malaria parasites can be present even in the absence of malaria, and since symptoms of malaria can be manifested even in the absence of malaria parasites, malaria diagnosis raises important issues for the adequate understanding of disease, etiology and diagnosis. One approach to the resolution of these issues adopts a realist view, according to which the needed clarifications will be derived from a careful representation of the entities on the side of the patient which form the ultimate truthmakers for clinical statements. We address a challenge to this realist approach relating to the diagnosis of malaria, and show how this challenge can be resolved by appeal to Basic Formal Ontology (BFO) and to the Ontology for General Medical Science (OGMS) constructed in its terms. http://dx.doi.org/10.1038/npre.2009.3960.1 Mon, 09 Nov 2009 10:30:10 UTC Malaria Diagnosis and the Plasmodium Life Cycle: the BFO Perspective doi:10.1038/npre.2009.3960.1 2009-11-09 Werner Ceusters Nature Precedings 2009-11-09T10:30:10Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3553.1 The collaborative, community-based Vaccine Ontology (VO) was developed to promote vaccine data standardization, integration, and computer-assisted reasoning. Currently VO covers a variety of aspects of the vaccine domain, with an emphasis on classification of vaccines and vaccine components, and on host immune response to vaccines. VO can be used for a number of applications, e.g., ontology-based vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI). http://dx.doi.org/10.1038/npre.2009.3553.1 Wed, 05 Aug 2009 18:50:32 UTC VO: Vaccine Ontology doi:10.1038/npre.2009.3553.1 2009-08-05 Yongqun He Nature Precedings 2009-08-05T18:50:32Z Manuscript Immunology Microbiology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3552.1 Vaccine research, as well as the development, testing, clinical trials, and commercial uses of vaccines involve complex processes with various biological data that include gene and protein expression, analysis of molecular and cellular interactions, study of tissue and whole body responses, and extensive epidemiological modeling. Although many data resources are available to meet different aspects of vaccine needs, it remains a challenge how we are to standardize vaccine annotation, integrate data about varied vaccine types and resources, and support advanced vaccine data analysis and inference. To address these problems, the community-based Vaccine Ontology (VO, http://www.violinet.org/vaccineontology) has been developed through collaboration with vaccine researchers and many national and international centers and programs, including the National Center for Biomedical Ontology (NCBO), the Infectious Disease Ontology (IDO) Initiative, and the Ontology for Biomedical Investigations (OBI). VO utilizes the Basic Formal Ontology (BFO) as the top ontology and the Relation Ontology (RO) for definition of term relationships. VO is represented in the Web Ontology Language (OWL) and edited using the Protégé-OWL. Currently VO contains more than 2000 terms and relationships. VO emphasizes on classification of vaccines and vaccine components, vaccine quality and phenotypes, and host immune response to vaccines. These reflect different aspects of vaccine composition and biology and can thus be used to model individual vaccines. More than 200 licensed vaccines and many vaccine candidates in research or clinical trials have been modeled in VO. VO is being used for vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI). Multiple VO applications will be presented. http://dx.doi.org/10.1038/npre.2009.3552.1 Wed, 05 Aug 2009 18:48:16 UTC VO: Vaccine Ontology doi:10.1038/npre.2009.3552.1 2009-08-05 Yongqun He Nature Precedings 2009-08-05T18:48:16Z Poster Biotechnology Immunology Microbiology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3476.1 An accurate classification of bacteria is essential for the proper identification of patient infections and subsequent treatment decisions. Multi-Locus Se-quence Typing (MLST) is a genetic technique for bacterial classification. MLST classifications are used to cluster bacteria into clonal complexes. Importantly, clonal complexes can serve as a biological species concept for bacteria, facilitating an otherwise difficult taxonomic classification. In this paper, we argue for the inclusion of terms relating to clonal complexes in biomedical ontologies. http://dx.doi.org/10.1038/npre.2009.3476.1 Mon, 27 Jul 2009 19:40:38 UTC Clonal Complexes in Biomedical Ontologies doi:10.1038/npre.2009.3476.1 2009-07-27 Albert Goldfain Nature Precedings 2009-07-27T19:40:38Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3475.1 This paper addresses a family of issues surrounding the biological phenomenon of resistance and its representation in realist ontologies. Resistance terms from various existing ontologies are examined and found to be either overly narrow, inconsistent, orotherwise problematic. We propose a more coherent ontological representation using the antibiotic resistance in Methicillin-Resistant Staphylococcus aureus (MRSa) as a case study. http://dx.doi.org/10.1038/npre.2009.3475.1 Mon, 27 Jul 2009 19:35:45 UTC Towards an Ontological Representation of Resistance: The Case of MRSa doi:10.1038/npre.2009.3475.1 2009-07-27 Albert Goldfain Nature Precedings 2009-07-27T19:35:45Z Presentation Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3474.1 This paper addresses a family of issues surrounding the biological phenomenon of resistance and its representation in realist ontologies. Resistance terms from various existing ontologies are examined and found to be either overly narrow, inconsistent, orotherwise problematic. We propose a more coherent ontological representation using the antibiotic resistance in Methicillin-Resistant Staphylococcus aureus (MRSa) as a case study. http://dx.doi.org/10.1038/npre.2009.3474.1 Mon, 27 Jul 2009 19:35:40 UTC Towards an Ontological Representation of Resistance: The Case of MRSa doi:10.1038/npre.2009.3474.1 2009-07-27 Albert Goldfain Nature Precedings 2009-07-27T19:35:40Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2027/version/2 Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology develop¬ment work being undertaken in support of scientific research. Ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But the ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, ontologies such as the GO are in different respects comparable to scientific theories, to scientific databases, and to scientific journal publications. Such a view implies a new conception of what is involved in the author¬ing, maintenance and application of ontologies in scientific contexts, and therewith also a new approach to the evaluation of ontologies and to the training of ontologists. http://precedings.nature.com/documents/2027/version/2 Wed, 16 Jul 2008 15:49:38 UTC Ontology (Science) hdl:10101/npre.2008.2027.2 2008-07-16 Barry Smith Nature Precedings 2008-07-16T15:49:38Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/1941/version/1 Numerous research groups are now utilizing Basic Formal Ontology (BFO) as an upper-level framework to assist in the organization and integration of biomedical information. This paper provides elucidation of the three BFO categories of function, role, and disposition, and considers two proposed sub-categories of artifactual function and bio-logical function. The motivation is to help advance the coherent treatment of functions, roles, and dispositions, to help provide the potential for more detailed classification, and to shed light on BFO’s general structure and use. http://precedings.nature.com/documents/1941/version/1 Tue, 03 Jun 2008 09:33:06 UTC Function, Role, and Disposition in Basic Formal Ontology hdl:10101/npre.2008.1941.1 2008-06-03 Robert Arp Nature Precedings 2008-06-03T09:33:06Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/