Integrating knowledge representation and quantitative modelling in physiology

Abstract

A wealth of potentially shareable resources, such as data and models, is being generated through the study of physiology by computational means. Although in principle the resources generated are reusable, in practice, few can currently be shared. A key reason for this disparity stems from the lack of consistent cataloguing and annotation of these resources in a standardised manner. Here, we outline our vision for applying community-based modelling standards in support of an automated integration of models across physiological systems and scales. Two key initiatives, the Physiome Project and the European contribution - the Virtual Phsysiological Human Project, have emerged to support this multiscale model integration, and we focus on the role played by two key components of these frameworks, model encoding and semantic metadata annotation. We present examples of biomedical modelling scenarios (the endocrine effect of atrial natriuretic peptide, and the implications of alcohol and glucose toxicity) to illustrate the role that encoding standards and knowledge representation approaches, such as ontologies, could play in the management, searching and visualisation of physiology models, and thus in providing a rational basis for healthcare decisions and contributing towards realising the goal of of personalized medicine.

On the Common Conceptual and Computational Frameworks for Multiscale Modeling

“…Project by the EU 58 . In this effort, a mechanism is developed to support the reuse and integration of physiological models across all the scales ranging from protein to whole body.…”

Improving the physiological realism of experimental models

“…The nature of the C-models developed within the Virtual Physiological Human (VPH) project [5][6][7] is in that sense somewhat different in that its objective is to develop predictive numerical tools to address medical rather than abstract scientific problems. First of all, this specific objective significantly raises the bar of admissible minimal level of C-model complexity.…”

“…First of all, this specific objective significantly raises the bar of admissible minimal level of C-model complexity. Suitable VPH C-models must ultimately mechanistically incorporate model output sensitivity towards, on the one hand, risk factors embedded in individual human genotypes and, on the other hand, therapeutic drug interactions [5][6][7]. In addition, it raises the need for species-specificity and detail of the quantitative database for VPH model development.…”

Unraveling liver complexity from molecular to organ level: Challenges and perspectives

“…So far multi-scale models are typically built by combining multiple mathematical and physical sub-models expressed in terms of mathematical equations, algorithmic concepts and components expressed as pseudo or source code and experimental or other input data in often proprietary software frameworks. However, in order to ensure reproducibility and allow for communication, exchange and collective development of multi-scale models, a model description language able to precisely describe each of these components is needed (de Bono and Hunter, 2012). While for certain sub-classes of models comprehensive and well-formulated description languages already exist, for example SBML and CellML for Boolean and ordinary differential equation (ODE) models, a similar language for multi-scale models still remains elusive.…”