FieldML, a proposed open standard for the Physiome project for mathematical model representation

Britten, Randall; Christie, G. Richard; Little, Caton; Miller, Andrew; Bradley, C P; Wu, Alan; Yu, Tingting; Hunter, Peter; Nielsen, Poul M. F.

doi:10.1007/s11517-013-1097-7

Cited by 29 publications

(27 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nearly all models are curated (checked to ensure that they have consistent units, they work and they give results consistent 280 with the reference publication) and many are annotated (the terms in the model are linked through metadata to ontologies that provide biological and biophysical meaning). The mathematical equations for the model can be displayed directly on the website or in OpenCOR, and the model equations can be output in a variety of computer languages (C, C++, Fortran, Matlab, Python) 18 . This repository, which includes FieldML models as well as 285…”

Section: Modelling Standardsmentioning

confidence: 99%

The Virtual Physiological Human: Ten Years After

Viceconti

Hunter

2016

Annu. Rev. Biomed. Eng.

Self Cite

View full text Add to dashboard Cite

Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of healthcare involves. The most challenging diseases, those with the largest 40 socioeconomic impact (cardiovascular conditions, musculoskeletal conditions, cancer, metabolic, immunity and neurodegenerative conditions) are all characterised by a complex genotype/phenotype interaction, and in general by a ÒsystemicÓ nature that the traditional reductionist approach struggle to cope with. In May 2005 a small group of researchers with different backgrounds met in Barcelona to discuss how the vision of computational 45 physiology promoted by the Physiome Project could be translated into the clinical practice.In that meeting the term Virtual Physiological Human was formally proposed. We know a lot about these diseases, but our knowledge is fragmentary as it is associated with molecular and cellular processes on the one hand, and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we 50 could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us to tame the complexity that such systemic behaviour involves. In 2005 this was simply not possible -the necessary methods and technologies were not available. Now, ten years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done. 55 KEYWORDS

show abstract

Section: Modelling Standardsmentioning

confidence: 99%

The Virtual Physiological Human: Ten Years After

Viceconti

Hunter

2016

Annu. Rev. Biomed. Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…This is particularly problematic, as the problems get bigger and more complex. The availability of tools like OpenCMISS [101], CARP (cardiac arrhythmia research package) [102], Cardiowave [103], FieldML [104], and SCIRun [105] suggests that some standards will be developed in time, but long-term, software maintenance, portability ,and user training remain obstacles to widespread adoption of a single tool. There is also concern that a given tool will lack the computational power for the problems of interest, and thus, many groups continue to use their own software.…”

Section: Developing Standardsmentioning

confidence: 99%

A Brief History of Tissue Models For Cardiac Electrophysiology

Henriquez

2014

IEEE Trans. Biomed. Eng.

View full text Add to dashboard Cite

The last four decades have produced a number of significant advances in the developments of computer models to simulate and investigate the electrical activity of cardiac tissue. The tissue descriptions that underlie these simulations have been built from a combination of clever insight and careful comparison with measured data at multiple scales. Tissue models have not only led to greater insights into the mechanisms of life-threatening arrhythmias but have been used to engineer new therapies to treat the consequences of cardiac disease. This paper is a look back at the early years in the cardiac modeling and the challenges facing the field as models move toward the clinic.

show abstract

“…The aim of these initiatives is not to develop one integrated model of a complete human being but rather to develop a framework in which models focusing on different organ systems and on different length/time scales can interact with each other. In order for this to happen, scientists active in the field of in silico medicine should agree on a set of standards [72] that will allow this interplay between different in silico models but also between in vitro, in vivo and in silico models. The trend towards personalised and precision medicine demands an ever increasing integration of all available information on the patients, ranging from life style over anatomy to genetics.…”

Section: Future Perspectivesmentioning

confidence: 99%

Regenerative orthopaedics: in vitro, in vivo … in silico

Geris

2014

International Orthopaedics (SICOT)

View full text Add to dashboard Cite

In silico, defined in analogy to in vitro and in vivo as those studies that are performed on a computer, is an essential step in problem solving and product development in classical engineering fields. The use of in silico models is now slowly easing its way into medicine. In silico models are already used in orthopaedics for the planning of complicated surgeries, personalised implant design and the analysis of gait measurements. However, these in silico models often lack the simulation of the response of the biological system over time. In silico models focusing on the response of the biological systems are in full development. This review starts with an introduction into in silico models of orthopaedic processes. Special attention is paid to the classification of models according to their spatiotemporal scale (gene/protein to population) and the information they were built on (data vs hypotheses). Subsequently, the review focusses on the in silico models used in regenerative orthopaedics research. Contributions of in silico models to an enhanced understanding and optimisation of four key elements -cells, carriers, culture and clinics -are illustrated. Finally, a number of challenges are identified, related to the computational aspects but also to the integration of in silico tools in clinical practice.

show abstract

FieldML, a proposed open standard for the Physiome project for mathematical model representation

Cited by 29 publications

References 38 publications

The Virtual Physiological Human: Ten Years After

The Virtual Physiological Human: Ten Years After

A Brief History of Tissue Models For Cardiac Electrophysiology

Regenerative orthopaedics: in vitro, in vivo … in silico

Contact Info

Product

Resources

About