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We introduce and define the Ontology of Physics for Biology (OPB), a reference ontology of physical principles that bridges the gap between bioinformat-ics modeling of biological structures and the bio-simulation modeling of biological processes. Where-as modeling anatomical entities is relatively well-studied, representing the physics-based semantics of(More)
As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of(More)
The integration of biomedical terminologies is indispensable to the process of information integration. When terminologies are linked merely through the alignment of their leaf terms, however, differences in context and ontological structure are ignored. Making use of the SNAP and SPAN ontologies, we show how three reference domain ontologies can be(More)
BACKGROUND We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. RESULTS We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have(More)
Short-term synaptic plasticity, which is common in the central nervous system, may contribute to the signal processing functions of both temporal integration and coincidence detection. For temporal integrators, whose output firng rate depends on a running average of recent synaptic inputs, plasticity modulates input synaptic strength and thus may directly(More)
There now exists a rich set of ontologies that provide detailed semantics for biological entities of interest. However, there is not (nor should there be) a single source ontology that provides all the necessary semantics for describing biological phenomena. In the domain of physiological biosimulation models, researchers use annotations to convey(More)
Currently, biosimulation researchers use a variety of computational environments and languages to model biological processes. Ideally, researchers should be able to semiautomatically merge models to more effectively build larger, multi-scale models. However, current modeling methods do not capture the underlying semantics of these models sufficiently to(More)
BACKGROUND Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such(More)
As a case-study of biosimulation model integration, we describe our experiences applying the SemSim methodology to integrate independently-developed, multiscale models of cardiac circulation. In particular, we have integrated the CircAdapt model (written by T. Arts for MATLAB) of an adapting vascular segment with a cardiovascular system model (written by M.(More)
Dynamic simulation models of physiology are often represented as a set of mathematical equations. Such models are very useful for studying and understanding the dynamic behavior of physiological variables. However, the sheer number of equations and variables can make these models unwieldy, difficult to under-stand, and challenging to maintain. We describe a(More)