Semantics-Based Composition of Integrated Cardiomyocyte Models Motivated by Real-World Use Cases

Abstract

Semantics-based model composition is an approach for generating complex biosimulation models from existing components that relies on capturing the biological meaning of model elements in a machine-readable fashion. This approach allows the user to work at the biological rather than computational level of abstraction and helps minimize the amount of manual effort required for model composition. To support this compositional approach, we have developed the SemGen software, and here report on SemGen’s semantics-based merging capabilities using real-world modeling use cases. We successfully reproduced a large, manually-encoded, multi-model merge: the “Pandit-Hinch-Niederer” (PHN) cardiomyocyte excitation-contraction model, previously developed using CellML. We describe our approach for annotating the three component models used in the PHN composition and for merging them at the biological level of abstraction within SemGen. We demonstrate that we were able to reproduce the original PHN model results in a semi-automated, semantics-based fashion and also rapidly generate a second, novel cardiomyocyte model composed using an alternative, independently-developed tension generation component. We discuss the time-saving features of our compositional approach in the context of these merging exercises, the limitations we encountered, and potential solutions for enhancing the approach.

Harmonizing semantic annotations for computational models in biology

“…Annotations have contributed to the successful reuse and exploration of models and data in tasks such as comparison 27,28 , interpretation 29 , retrieval [30][31][32] , integration [33][34][35][36][37] , simulation 38 , translation between formats 29,37,[39][40][41][42] (see also http://sbfc.sourceforge.net/mediawiki/index.php/SBML2BioPAX), and visualization 37,[43][44][45] . Semantic annotations are also a key component for model-driven design of synthetic biological systems where they are used in model composition tasks when constructing optimum biological systems built from models 41,[45][46][47][48] .…”

“…Another set of barriers are associated with model-to-model integration. Composing new models from existing models remains a largely manual and error-prone process, and recent work has demonstrated how it can be accelerated using semantic annotations 31,34,36,60 . By examining annotations, software tools can recognize where models overlap in their biological content and then provide recommendations about how the models could be coupled.…”

Semi-automated Modular Program Constructor for physiological modeling: Building cell and organ models

“…This update has the following changes: Updated submission to use more consistent and unifying wording throughout the paper for terms like model, modules, software; added a brief discussion on other modularity software tools in the Introduction; added a sentence on archiving modules, clarified confusing sentences, added reference from ML Neal et al 2015, and one minor update to Figure 1.…”

“…It relies on the user to resolve discrepancies between models. SemanticSBML(Krause 2010), SemGen (Genari 2011, Neal 2015, and Phy-Sim (Erson 2012) make use of standard semantic and ontological descriptions of a biological model to allow large models to be broken down easily, without much user guidance, into biologically meaningful components linked to their mathematical description. Semantic and ontological metadata assists the construction of new models by providing suggested connections or relationships between models.…”

Epithelial Modelling Platform: A Tool for Model Discovery and Assembly with the Physiome Model Repository

“…libCellML is a library to serialize, validate, and instantiate a CellML model. A great deal of previous research on model composition is investigated in (Neal et al, 2015;Gennari et al, 2008;Neal et al, 2009;Krause et al, 2010;Coskun et al, 2013).…”