The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions

Bono, Bernard de; Hoehndorf, Robert; Wimalaratne, Sarala M.; Gkoutos, Georgios V.; Grenon, Pierre

doi:10.1186/1756-0500-4-313

Cited by 34 publications

(37 citation statements)

References 47 publications

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“…However, there are thousands of ontological terms, so to help the user choose a suitable ontological term, a search term or a regular expression can be entered, for the view to use to retrieve a list of matching terms from different ontologies. The retrieval itself is done by sending a request to an instance of RICORDO (ricordo.eu; de Bono et al, 2011). Using that list, the user can decide which ontological term to use, after looking it up, if needed (as illustrated in Figure 4 by looking up the “voltage-gated sodium channel complex” term from the GO ontology).…”

Section: Resultsmentioning

confidence: 99%

OpenCOR: a modular and interoperable approach to computational biology

Garny

Hunter

2015

Front. Physiol.

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Computational biologists have been developing standards and formats for nearly two decades, with the aim of easing the description and exchange of experimental data, mathematical models, simulation experiments, etc. One of those efforts is CellML (cellml.org), an XML-based markup language for the encoding of mathematical models. Early CellML-based environments include COR and OpenCell. However, both of those tools have limitations and were eventually replaced with OpenCOR (opencor.ws). OpenCOR is an open source modeling environment that is supported on Windows, Linux and OS X. It relies on a modular approach, which means that all of its features come in the form of plugins. Those plugins can be used to organize, edit, simulate and analyze models encoded in the CellML format. We start with an introduction to CellML and two of its early adopters, which limitations eventually led to the development of OpenCOR. We then go onto describing the general philosophy behind OpenCOR, as well as describing its openness and its development process. Next, we illustrate various aspects of OpenCOR, such as its user interface and some of the plugins that come bundled with it (e.g., its editing and simulation plugins). Finally, we discuss some of the advantages and limitations of OpenCOR before drawing some concluding remarks.

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Section: Resultsmentioning

confidence: 99%

OpenCOR: a modular and interoperable approach to computational biology

Garny

Hunter

2015

Front. Physiol.

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“…as discussed in [63]) and intervening flow routes, a knowledge combination referred to as a physiology circuitboard. This standardized physiome circuitboard would, therefore, support interoperability for:…”

Section: Short-range Flowmentioning

confidence: 99%

A physiome interoperability roadmap for personalized drug development

et al. 2016

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One contribution of 12 to a theme issue 'The Human Physiome: a necessary key to the creative destruction of medicine'. The goal of developing therapies and dosage regimes for characterized subgroups of the general population can be facilitated by the use of simulation models able to incorporate information about inter-individual variability in drug disposition (pharmacokinetics), toxicity and response effect (pharmacodynamics). Such observed variability can have multiple causes at various scales, ranging from gross anatomical differences to differences in genome sequence. Relevant data for many of these aspects, particularly related to molecular assays (known as '-omics'), are available in online resources, but identification and assignment to appropriate model variables and parameters is a significant bottleneck in the model development process. Through its efforts to standardize annotation with consequent increase in data usability, the human physiome project has a vital role in improving productivity in model development and, thus, the development of personalized therapy regimes. Here, we review the current status of personalized medicine in clinical practice, outline some of the challenges that must be overcome in order to expand its applicability, and discuss the relevance of personalized medicine to the more widespread challenges being faced in drug discovery and development. We then review some of (i) the key data resources available for use in model development and (ii) the potential areas where advances made within the physiome modelling community could contribute to physiologically based pharmacokinetic and physiologically based pharmacokinetic/pharmacodynamic modelling in support of personalized drug development. We conclude by proposing a roadmap to further guide the physiome community in its on-going efforts to improve data usability, and integration with modelling efforts in the support of personalized medicine development.

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“…The ability to consistently navigate and query a set of data and model resources using terms taken from one or more ontologies is called semantic interoperability (Box 1). Together, ontologies, standard formats, and associated infrastructure enable automated reasoning: the translation of human-meaningful queries to machine-processing of the relevant parts of vast data and model resources (de Bono et al, 2011). One such application could be a protocol that clamps all intra-and extra-cellular ion concentrations, without needing to know which ion species are included in each model.…”

Section: Provide Semantically Rich Interfaces Between Models and Expementioning

confidence: 99%

“…Semantic interoperability (where "semantic" means "relating to meaning") denotes the ability to consistently navigate and query a set of data, model and protocol resources using terms taken from one or more ontologies (de Bono et al, 2011). With ontological annotation, new knowledge automatically connects to that which already exists, so that users can discover relevant knowledge without knowing its location in advance, and without having to formulate specific queries to link and select data.…”

Section: Box 1: Terminologymentioning

confidence: 99%

“…To achieve this, connections between protocol and model descriptions need to be done at the level of biological concepts, rather than depending on details of a particular encoding . What is needed is a common language between models and protocols (and researchers), and fortunately this already exists (de Bono et al, 2011) through the use of ontological annotation (see Box 1). Such an unambiguous identification of every variable, parameter or process in a model, data set or experimental procedure is already in place for many models in the BioModels database (Li et al, 2010).…”

Section: Provide Semantically Rich Interfaces Between Models and Expementioning

confidence: 99%

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A call for virtual experiments: Accelerating the scientific process

Cooper

Vik

Waltemath

2015

Progress in Biophysics and Molecular Biology

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Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. We argue that promoting the reuse of virtual experiments (the in silico analogues of wet-lab or field experiments) would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the translational application of models. A key step towards achieving this is that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. Lastly, we outline how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, transforming our approach to systems biology. Dear Sirs,We enclose a manuscript titled "A call for virtual experiments: accelerating the scientific process" for inclusion within the Special Issue on "Multi-bio and multi-scale systems biology" in Progress in Biophysics and Molecular Biology. In it we propose the concept of "virtual experiments" as the in silico analogues of wet-lab or field experiments, and argue that this concept deserves as much attention as the computational models to which such experiments are applied. Promoting the reuse of virtual experiments would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists.Experiments are fundamental to the scientific method, whether for exploration, description or explanation. Experiments should therefore be as central in computational biology as in other sciences, for studying the implications of theories or hypotheses encoded as computational models. In current practice, however, experiments applied to models are usually embedded in opaque computer code, which is often not available for public scrutiny. We discuss how the protocol for a computational experiment should be viewed as an entity in its own right, and cleanly separated from the description of the model itself, and from surrounding code. Annotations can then facilitate the linking of models to experiment descriptions and any corresponding data available.This approach can provide many benefits for scientific progress: in specifying, assaying, and comparing the behavioural repertoires of models; as a prerequisite for reproducible research; to guide model reuse and composition; and for quality assurance in the application of computational biology models. The paper lays out these benefits to motivate wider adoption and tool support for virtual experiments. We also present a "vision of the future" in which virtual experim...

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The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions

Cited by 34 publications

References 47 publications

OpenCOR: a modular and interoperable approach to computational biology

OpenCOR: a modular and interoperable approach to computational biology

A physiome interoperability roadmap for personalized drug development

A call for virtual experiments: Accelerating the scientific process

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