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1.
Front Physiol ; 13: 795303, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-35547570

RESUMEN

We present (i) the ApiNATOMY workflow to build knowledge models of biological connectivity, as well as (ii) the ApiNATOMY TOO map, a topological scaffold to organize and visually inspect these connectivity models in the context of a canonical architecture of body compartments. In this work, we outline the implementation of ApiNATOMY's knowledge representation in the context of a large-scale effort, SPARC, to map the autonomic nervous system. Within SPARC, the ApiNATOMY modeling effort has generated the SCKAN knowledge graph that combines connectivity models and TOO map. This knowledge graph models flow routes for a number of normal and disease scenarios in physiology. Calculations over SCKAN to infer routes are being leveraged to classify, navigate and search for semantically-linked metadata of multimodal experimental datasets for a number of cross-scale, cross-disciplinary projects.

2.
Front Neuroinform ; 15: 560050, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33664662

RESUMEN

We present a framework for the topological and semantic assembly of multiscale physiology route maps. The framework, called ApiNATOMY, consists of a knowledge representation (KR) model and a set of knowledge management (KM) tools. Using examples of ApiNATOMY route maps, we present a KR format that is suitable for the analysis and visualization by KM tools. The conceptual KR model provides a simple method for physiology experts to capture process interactions among anatomical entities. In this paper, we outline the KR model, modeling format, and the KM procedures to translate concise abstraction-based specifications into fully instantiated models of physiology processes.

3.
Front Physiol ; 6: 24, 2015.
Artículo en Inglés | MEDLINE | ID: mdl-25759670

RESUMEN

A key challenge for the physiology modeling community is to enable the searching, objective comparison and, ultimately, re-use of models and associated data that are interoperable in terms of their physiological meaning. In this work, we outline the development of a workflow to modularize the simulation of tissue-level processes in physiology. In particular, we show how, via this approach, we can systematically extract, parcellate and annotate tissue histology data to represent component units of tissue function. These functional units are semantically interoperable, in terms of their physiological meaning. In particular, they are interoperable with respect to [i] each other and with respect to [ii] a circuitboard representation of long-range advective routes of fluid flow over which to model long-range molecular exchange between these units. We exemplify this approach through the combination of models for physiology-based pharmacokinetics and pharmacodynamics to quantitatively depict biological mechanisms across multiple scales. Links to the data, models and software components that constitute this workflow are found at http://open-physiology.org/.

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