e-Science and biological pathway semantics

<p>Abstract</p> <p>Background</p> <p>The development of e-Science presents a major set of opportunities and challenges for the future progress of biological and life scientific research. Major new tools are required and corresponding demands are placed on the high-throughput data generated and used in these processes. Nowhere is the demand greater than in the semantic integration of these data. Semantic Web tools and technologies afford the chance to achieve this semantic integration. Since pathway knowledge is central to much of the scientific research today it is a good test-bed for semantic integration. Within the context of biological pathways, the BioPAX initiative, part of a broader movement towards the standardization and integration of life science databases, forms a necessary prerequisite for its successful application of e-Science in health care and life science research. This paper examines whether BioPAX, an effort to overcome the barrier of disparate and heterogeneous pathway data sources, addresses the needs of e-Science.</p> <p>Results</p> <p>We demonstrate how BioPAX pathway data can be used to ask and answer some useful biological questions. We find that BioPAX comes close to meeting a broad range of e-Science needs, but certain semantic weaknesses mean that these goals are missed. We make a series of recommendations for re-modeling some aspects of BioPAX to better meet these needs.</p> <p>Conclusion</p> <p>Once these semantic weaknesses are addressed, it will be possible to integrate pathway information in a manner that would be useful in e-Science.</p

Ontology driven integration platform for clinical and translational research

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a dynamic and distributed environment. Components of the semantic solution and its overall architecture are described

Structuring an event ontology for disease outbreak detection

<p>Abstract</p> <p>Background</p> <p>This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is designed to support timely detection of disease outbreaks and rapid judgment of their alerting status by 1) bridging a gap between layman's language used in disease outbreak reports and public health experts' deep knowledge, and 2) making multi-lingual information available.</p> <p>Construction and content</p> <p>This event ontology integrates a model of experts' knowledge for disease surveillance, and at the same time sets of linguistic expressions which denote disease-related events, and formal definitions of events. In this ontology, rather general event classes, which are suitable for application to language-oriented tasks such as recognition of event expressions, are placed on the upper-level, and more specific events of the experts' interest are in the lower level. Each class is related to other classes which represent participants of events, and linked with multi-lingual synonym sets and axioms.</p> <p>Conclusions</p> <p>We consider that the design of the event ontology and the methodology introduced in this paper are applicable to other domains which require integration of natural language information and machine support for experts to assess them. The first version of the ontology, with about 40 concepts, will be available in March 2008.</p

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

Spatio-structural granularity of biological material entities

<p>Abstract</p> <p>Background</p> <p>With the continuously increasing demands on knowledge- and data-management that databases have to meet, ontologies and the theories of granularity they use become more and more important. Unfortunately, currently used theories and schemes of granularity unnecessarily limit the performance of ontologies due to two shortcomings: (i) they do not allow the integration of multiple granularity perspectives into one granularity framework; (ii) they are not applicable to cumulative-constitutively organized material entities, which cover most of the biomedical material entities.</p> <p>Results</p> <p>The above mentioned shortcomings are responsible for the major inconsistencies in currently used spatio-structural granularity schemes. By using the Basic Formal Ontology (BFO) as a top-level ontology and Keet's general theory of granularity, a granularity framework is presented that is applicable to cumulative-constitutively organized material entities. It provides a scheme for granulating complex material entities into their constitutive and regional parts by integrating various compositional and spatial granularity perspectives. Within a scale dependent resolution perspective, it even allows distinguishing different types of representations of the same material entity. Within other scale dependent perspectives, which are based on specific types of measurements (e.g. weight, volume, etc.), the possibility of organizing instances of material entities independent of their parthood relations and only according to increasing measures is provided as well. All granularity perspectives are connected to one another through overcrossing granularity levels, together forming an integrated whole that uses the <it>compositional object perspective </it>as an integrating backbone. This granularity framework allows to consistently assign structural granularity values to all different types of material entities.</p> <p>Conclusions</p> <p>The here presented framework provides a spatio-structural granularity framework for all domain reference ontologies that model cumulative-constitutively organized material entities. With its multi-perspectives approach it allows querying an ontology stored in a database at one's own desired different levels of detail: The contents of a database can be organized according to diverse granularity perspectives, which in their turn provide different <it>views </it>on its content (i.e. data, knowledge), each organized into different levels of detail.</p

Evolution and Taxonomic Classification of Human Papillomavirus 16 (HPV16)-Related Variant Genomes: HPV31, HPV33, HPV35, HPV52, HPV58 and HPV67

Human papillomavirus 16 (HPV16) species group (alpha-9) of the Alphapapillomavirus genus contains HPV16, HPV31, HPV33, HPV35, HPV52, HPV58 and HPV67. These HPVs account for 75% of invasive cervical cancers worldwide. Viral variants of these HPVs differ in evolutionary history and pathogenicity. Moreover, a comprehensive nomenclature system for HPV variants is lacking, limiting comparisons between studies.DNA from cervical samples previously characterized for HPV type were obtained from multiple geographic regions to screen for novel variants. The complete 8 kb genomes of 120 variants representing the major and minor lineages of the HPV16-related alpha-9 HPV types were sequenced to capture maximum viral heterogeneity. Viral evolution was characterized by constructing phylogenic trees based on complete genomes using multiple algorithms. Maximal and viral region specific divergence was calculated by global and pairwise alignments. Variant lineages were classified and named using an alphanumeric system; the prototype genome was assigned to the A lineage for all types.The range of genome-genome sequence heterogeneity varied from 0.6% for HPV35 to 2.2% for HPV52 and included 1.4% for HPV31, 1.1% for HPV33, 1.7% for HPV58 and 1.1% for HPV67. Nucleotide differences of approximately 1.0% - 10.0% and 0.5%-1.0% of the complete genomes were used to define variant lineages and sublineages, respectively. Each gene/region differs in sequence diversity, from most variable to least variable: noncoding region 1 (NCR1) /noncoding region 2 (NCR2) >upstream regulatory region (URR)> E6/E7 > E2/L2 > E1/L1.These data define maximum viral genomic heterogeneity of HPV16-related alpha-9 HPV variants. The proposed nomenclature system facilitates the comparison of variants across epidemiological studies. Sequence diversity and phylogenies of this clinically important group of HPVs provides the basis for further studies of discrete viral evolution, epidemiology, pathogenesis and preventative/therapeutic interventions

Differing Endoplasmic Reticulum Stress Response to Excess Lipogenesis versus Lipid Oversupply in Relation to Hepatic Steatosis and Insulin Resistance

Mitochondrial dysfunction and endoplasmic reticulum (ER) stress have been implicated in hepatic steatosis and insulin resistance. The present study investigated their roles in the development of hepatic steatosis and insulin resistance during de novo lipogenesis (DNL) compared to extrahepatic lipid oversupply. Male C57BL/6J mice were fed either a high fructose (HFru) or high fat (HFat) diet to induce DNL or lipid oversupply in/to the liver. Both HFru and HFat feeding increased hepatic triglyceride within 3 days (by 3.5 and 2.4 fold) and the steatosis remained persistent from 1 week onwards (p<0.01 vs Con). Glucose intolerance (iAUC increased by ∼60%) and blunted insulin-stimulated hepatic Akt and GSK3β phosphorylation (∼40–60%) were found in both feeding conditions (p<0.01 vs Con, assessed after 1 week). No impairment of mitochondrial function was found (oxidation capacity, expression of PGC1α, CPT1, respiratory complexes, enzymatic activity of citrate synthase & β-HAD). As expected, DNL was increased (∼60%) in HFru-fed mice and decreased (32%) in HFat-fed mice (all p<0.05). Interestingly, associated with the upregulated lipogenic enzymes (ACC, FAS and SCD1), two (PERK/eIF2α and IRE1/XBP1) of three ER stress pathways were significantly activated in HFru-fed mice. However, no significant ER stress was observed in HFat-fed mice during the development of hepatic steatosis. Our findings indicate that HFru and HFat diets can result in hepatic steatosis and insulin resistance without obvious mitochondrial defects via different lipid metabolic pathways. The fact that ER stress is apparent only with HFru feeding suggests that ER stress is involved in DNL per se rather than resulting from hepatic steatosis or insulin resistance