Multiscale modeling for biologists

Meier‐Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

doi:10.1002/wsbm.33

Cited by 109 publications

(76 citation statements)

References 57 publications

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“…With time one can reasonably expect the number of such examples and the kinds of knowledge integrated to increase. Models also make it possible to connect affects across length scales, such as from the cytoskeletal components to cells to tissues to whole embryos [21,24,[67][68][69].…”

Section: Integrate Knowledgementioning

confidence: 99%

How computational models can help unlock biological systems

Brodland

2015

Seminars in Cell & Developmental Biology

197

119

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With computation models playing an ever increasing role in the advancement of science, it is important that researchers understand what it means to model something; recognize the implications of the conceptual, mathematical and algorithmic steps of model construction; and comprehend what models can and cannot do. Here, we use examples to show that models can serve a wide variety of roles, including hypothesis testing, generating new insights, deepening understanding, suggesting and interpreting experiments, tracing chains of causation, doing sensitivity analyses, integrating knowledge, and inspiring new approaches. We show that models can bring together information of different kinds and do so across a range of length scales, as they do in multi-scale, multi-faceted embryogenesis models, some of which connect gene expression, the cytoskeleton, cell properties, tissue mechanics, morphogenetic movements and phenotypes. Models cannot replace experiments nor can they prove that particular mechanisms are at work in a given situation. But they can demonstrate whether or not a proposed mechanism is sufficient to produce an observed phenomenon. Although the examples in this article are taken primarily from the field of embryo mechanics, most of the arguments and discussion are applicable to any form of computational modelling.

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Section: Integrate Knowledgementioning

confidence: 99%

How computational models can help unlock biological systems

Brodland

2015

Seminars in Cell & Developmental Biology

197

119

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“…As regards multi-scale modeling of cells, different scales can be combined with the appropriate computational modeling techniques and available software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling, as previously reviewed (Meier-Schellersheim et al 2009). Top-down and bottom-up (from the system to the subsystems and viceversa) approaches co-exist, as well as deductive and phenomenological terms in the typical hybrid models for the more comprehensive descriptions of cell behavior.…”

Section: Multi-scale Modeling Of Cell Behaviormentioning

confidence: 99%

“…Thermodynamic, soft potential and stochastic models help to address molecular interactions such as DNA transitions, cellular locomotion (see Sect. 7.5), the kinetics of enzymes and their behavior as molecular machines or gene expression processes and their random variations, among other phenomena (Nelson 2004;Meier-Schellersheim et al 2009). …”

Section: Multi-scale Modeling Of Cell Behaviormentioning

confidence: 99%

Multi-scale and Multi-physical/Biochemical Modeling in Bio-MEMS

Lantada

2016

Microsystems for Enhanced Control of Cell Behavior

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Multidisciplinarity is intrinsic to Biomedical Engineering, as the products, processes and systems of the biomedical industry, aimed at continuously improving the diagnosis, treatment and prevention of pathologies, are normally developed by large teams of physicians, biologists, materials scientists and engineers. In the field of biomedical microsystems (bio-MEMS) for interacting at a cellular and even molecular level, several physical, chemical and biological phenomena are present and an adequate comprehension of the behaviour of such microdevices also requires studying interactions between the microdevices and the surrounding environments at different scale levels. In such complex systems, the use of modeling resources may be a key aspect towards a straightforward and successful development process. As modern (bio)engineering systems usually exploit phenomena at different scales for improving functionalities of traditional systems, linking the different scales and using multi-scale modeling approaches can increase the predictive capability and applicability of modeling to a wide range of applications. In addition, as modern (bio)engineering systems typically involve different areas of Physics and Chemistry, understanding and modeling their behavior requires the use of multi-physical/chemical modeling approaches. Only by being able to describe the behavior of such (bio)engineering systems at different scale levels and taking account of the physical and chemical phenomena involved in their operation, can we benefit from the advantages of (computer-aided) modeling regarding cost saving, reduction of time-to-market and overall understanding of the products, processes and systems under development. This chapter details methods and examples and provides some cases of study linked to the use of multi-scale and multi-physical/chemical modeling approaches in the field of biomedical microsystems for interacting at a cellular and even molecular level, as introduction to procedures used thoroughly along the Handbook.

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“…Multiscale, hybrid processes in biosystems and in human-built process networks contain more complex elements and structures, than the theoretically established mathematical constructs. Moreover, the execution of the hybrid, discrete/continuous and optionally multiscale models is a difficult question, because the usual integrators do not tolerate the discrete events, while the usual representation of the continuous processes cannot be embedded into the discrete models conveniently (Meier-Schellersheim et al, 2009). Another challenge is the effective combination of quantitative models with rule-based qualitative knowledge.…”

Section: Direct Computer Mapping Of the Investigated Problemmentioning

confidence: 99%

Preparation of a dynamic simulation model to support decision making in a sensitive rural area

Varga

Balogh

Csukás

2015

JAI

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A B S T R A C TThis paper focuses on the demonstration of a conceptual framework and a dynamic simulation based tool, through the example of southern catchment basin of Lake Balaton. The objective is to support the sustainable and reasonable environmental management by model based investigation of various scenarios. In the developed hydrological model, the coherence is given by the compartmentalized dynamic network of water flows and water bodies. The completeness is solved by the complete and disjoint covering of the whole area by modeled patches, corresponding to the CORINE land cover database of natural and human built environment. The complexity of the large scale and long term processes is managed by evaluating detailed models only for one representative patch from each class, while the calculation of the similar patches is solved by simple multiplication rules. According to the first experiences, the developed framework is able to integrate the field experts' knowledge (data, relations, empirical knowledge, etc.) for the prediction of land use effects besides different climatic scenarios. It is noted, that continuous extension and refinement of the model and of the involved data is necessary, especially through more realistic case studies.

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Multiscale modeling for biologists

Cited by 109 publications

References 57 publications

How computational models can help unlock biological systems

How computational models can help unlock biological systems

Multi-scale and Multi-physical/Biochemical Modeling in Bio-MEMS

Preparation of a dynamic simulation model to support decision making in a sensitive rural area

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