http://precedings.nature.com/tags/Infectious%20disease Recently posted documents tagged with 'Infectious disease' 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.2009.3553.1 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.2009.3464.1 We are developing a set of ontologies that deal with vector-borne diseases and the arthropod vectors that transmit them. For practical reasons (application priorities), we initiated this project with an ontology of insecticide resistance followed by a series of ontologies that describe malaria as well as physiological processes of mosquitoes that are relevant to, and involved in, disease transmission. These will be expanded to encompass other vector-borne diseases as well as non-mosquito vectors. The aim of the whole undertaking, which is worked out in the frame of the international IDO (Infectious Disease Ontology) project, is to provide the community with a set of ontological tools that can be used both in the development of specific databases and, most importantly, in the construction of decision support systems to control these diseases. http://dx.doi.org/10.1038/npre.2009.3464.1 Mon, 27 Jul 2009 20:21:49 UTC A set of ontologies to drive tools for the control of vector-borne diseases doi:10.1038/npre.2009.3464.1 2009-07-27 Pantelis Topalis Nature Precedings 2009-07-27T20:21:49Z Manuscript 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/1910/version/1 Vaccines capable of controlling neoplastic and infectious diseases which depend on the cellular immune response for their resolution, have proven difficult to develop. We, and others, have previously demonstrated that the potent immunogenicity of hepatitis B surface antigen (HBsAg), the already- licensed human vaccine for hepatitis B infection, may be exploited to deliver foreign antigens for cytotoxic T-lymphocyte (CTL) induction. In this study we demonstrate that recombinant (r) HBsAg DNA delivering a CTL polyepitope appended at the C’ terminus elicits concomitant responses to multiple epitopes restricted through a diversity of MHC class I haplotypes, which are relevant in a number of human diseases. We show that the rHBsAg DNA vaccine elicits concomitant protection against neoplastic and infectious disease. These studies vindicate the use of HBsAg as a powerful vector to deliver CTL responses to foreign antigens, and have implications for a multi-disease vaccine applicable to the HLA-polymorphic human population. http://precedings.nature.com/documents/1910/version/1 Tue, 27 May 2008 16:15:31 UTC HBsAg-vectored DNA vaccines elicit concomitant protective responses to multiple CTL epitopes relevant in human disease. hdl:10101/npre.2008.1910.1 2008-05-27 Robert R. Tindle Nature Precedings 2008-05-27T16:15:31Z Manuscript Biotechnology Cancer Immunology http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2007.1373.1 The Centers for Disease Control (CDC) is currently attempting to eliminate syphilis in the United States (US); to ensure that their control strategies will be effective it is important to understand the transmission dynamics of syphilis. Epidemics of certain infectious diseases (e.g., influenza) can rise and fall with a well-defined periodicity; this cycling behavior is important because it can have significant implications for the design and effectiveness of control strategies. Here we discuss the methodology that has been used to identify epidemic cycles in longitudinal data sets, and the endogenous and exogenous mechanisms that generate cycling. We then examine the recently proposed hypothesis that syphilis epidemics cycle. This hypothesis was proposed based upon the results of a spectral analysis of a longitudinal data set that had been collected by the (CDC), and the analysis of a syphilis transmission model. We use spectral analysis to reanalyze the CDC’s data set, as well as to analyze a longitudinal mortality data set provided by the CDC. We also use published transmission models to predict the expected dynamics of syphilis epidemics. In contrast to the previous findings we find that: (i) that neither of the CDC’s data sets provide compelling evidence that syphilis epidemics cycle and (ii) published transmission models predict that syphilis epidemics should monotonically decrease (as a function of the treatment rate) rather than cycle. We explain the reasons why previous authors had proposed that syphilis epidemics cycle. Finally, we discuss the implications of our findings regarding the transmission dynamics of syphilis for the CDC’s elimination plan. http://dx.doi.org/10.1038/npre.2007.1373.1 Fri, 30 Nov 2007 18:29:36 UTC The transmission dynamics of syphilis and the CDC’s elimination plan doi:10.1038/npre.2007.1373.1 2007-11-30 Virginie Supervie Nature Precedings 2007-11-30T18:29:36Z Manuscript Ecology http://creativecommons.org/licenses/by/3.0/