GemCell: A generic platform for modeling multi-cellular biological systems

Amir-Kroll, Hila; Sadot, Avital; Cohen, Irun R.; Harel, David

doi:10.1016/j.tcs.2007.11.014

Cited by 16 publications

(16 citation statements)

References 20 publications

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“…This technique enables study of complex systems in a simplified manner, because its implementation merely requires measurable inputs and outputs, without quantifying the response of each component inside the box. Approaches based on this concept are highly useful for describing engineered systems and were also applied for studying some biological systems, such as signal transduction in the osmoadaptation pathway of yeast (6) and agentbased modeling of multicellular interactions (7). Here, we apply the black box approach to construct a predictive model of cell differentiation.…”

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confidence: 99%

Diverse continuum of CD4⁺T-cell states is determined by hierarchical additive integration of cytokine signals

Eizenberg-Magar

Rimer

Zaretsky

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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During cell differentiation, progenitor cells integrate signals from their environment that guide their development into specialized phenotypes. The ways by which cells respond to complex signal combinations remain difficult to analyze and model. To gain additional insight into signal integration, we systematically mapped the response of CD4 + T cells to a large number of input cytokine combinations that drive their differentiation. We find that, in response to varied input combinations, cells differentiate into a continuum of cell fates as opposed to a limited number of discrete phenotypes. Input cytokines hierarchically influence the cell population, with TGFβ being most dominant followed by IL-6 and IL-4. Mathematical modeling explains these results using additive signal integration within hierarchical groups of input cytokine combinations and correctly predicts cell population response to new input conditions. These findings suggest that complex cellular responses can be effectively described using a segmented linear approach, providing a framework for prediction of cellular responses to new cytokine combinations and doses, with implications to fine-tuned immunotherapies.C ell differentiation is controlled by complex gene regulatory networks that determine the expression of a large number of genes in response to external stimuli. CD4 + T cells, central regulators of immune responses, can differentiate into a number of phenotypes (or cell states), each defined by the expression of a panel of genes, such as lineage-specifying transcription factors (TFs) and cytokines (1). Differentiation outcome depends on a number of factors, including strength of antigen stimulation (2, 3), interactions with antigen presenting cells, and the signaling environment defined by secreted cytokines (1). By applying specific cytokine signals, it is possible to direct antigen-activated T cells toward differentiation into a number of specific phenotypes. Although the molecular interactions and regulatory networks that govern the differentiation process are being revealed at increasing resolution (4, 5), understanding the logic of operation of these complex networks and developing predictive mathematical models for cellular responses remain a challenge.Mathematical models that describe complex cellular processes are difficult to construct because of a lack of complete information about the underlying networks of molecular interactions and in particular, missing quantitative data regarding the parameters of biochemical interactions within these networks. Alternatively, a "black box" approach can be used, constructing a model of the system by analyzing its response to different input conditions (Fig. 1A). This technique enables study of complex systems in a simplified manner, because its implementation merely requires measurable inputs and outputs, without quantifying the response of each component inside the box. Approaches based on this concept are highly useful for describing engineered systems and were also applied for studying som...

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mentioning

confidence: 99%

Diverse continuum of CD4⁺T-cell states is determined by hierarchical additive integration of cytokine signals

Eizenberg-Magar

Rimer

Zaretsky

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…After a predefined time interval, the team object generates another event for the statecharts of each of the team members. Upon entering the Jumping state, ST notifies FE to animate the action (2). Consequently, the animated team leader jumps, and the team members follow suit.…”

Section: Discussionmentioning

confidence: 99%

“…The swim message enables a forbidden element in the run LSC, causing the run LSC to exit. Again, the swim LSC notifies ST, which in turn notifies FE (2). The flood LSC completes after it instructs the team to walk, the environment to end the flood, and the team to stand (i.e., to stop moving).…”

Section: Discussionmentioning

confidence: 99%

“…In case a fast speed action is taken, each of the two team member objects will enter a resting state after some time. Consequently, ST notifies SC(6) and FE (2). Concurrently, the team member in FE changes its appearance to resting, an SC in SC is triggered, and it notifies FE (5) to activate the team member's camera.…”

Section: Discussionmentioning

confidence: 99%

“…We use the generic reactive animation architecture to visualize behaviors as part of the GemCell project [2]. GemCell contains a generic statechart model of cell behavior, which captures the five main aspects of cell behavior (proliferation, death, movement, import and export).…”

Section: Additional Ra Examplesmentioning

confidence: 99%

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Generic Reactive Animation: Realistic Modeling of Complex Natural Systems

Harel

Setty

Formal Methods in Systems Biology

Self Cite

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Abstract. Natural systems, such as organs and organisms, are largescale complex systems with numerous elements and interactions. Modeling such systems can lead to better understanding thereof and may help in efforts to save on resources and development time. In recent years, our group has been involved in modeling and understanding biological systems, which are perhaps the prime example of highly complex and reactive large-scale systems. To handle their complexity, we developed a technique called reactive animation (RA), which smoothly connects a reactive system engine to an animation tool, and which has been described in earlier publications. In the present paper we show how the basic idea of RA can be made generic, by providing a simple general way to link up any number of reactive system engines -even ones that are quite different in nature -to an animation tool. This results in natural-looking, fully interactive 3D animations, driven by complex reactive systems running in the background. We illustrate this with two examples that link several tools: Rhapsody for state-based specification, the Play-Engine for scenario-based specification, MATLAB for mathematical analysis and the 3DGameStudio for animation. Our examples are both from biology (pancreatic development) and from everyday activities (e.g., gym training).

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Multiscale modeling for biologists

Meier‐Schellersheim

Fraser

Klauschen

2009

WIREs Mechanisms of Disease

109

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Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling.

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GemCell: A generic platform for modeling multi-cellular biological systems

Cited by 16 publications

References 20 publications

Diverse continuum of CD4⁺T-cell states is determined by hierarchical additive integration of cytokine signals

Diverse continuum of CD4⁺T-cell states is determined by hierarchical additive integration of cytokine signals

Generic Reactive Animation: Realistic Modeling of Complex Natural Systems

Multiscale modeling for biologists

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GemCell: A generic platform for modeling multi-cellular biological systems

Cited by 16 publications

References 20 publications

Diverse continuum of CD4+T-cell states is determined by hierarchical additive integration of cytokine signals

Diverse continuum of CD4+T-cell states is determined by hierarchical additive integration of cytokine signals

Generic Reactive Animation: Realistic Modeling of Complex Natural Systems

Multiscale modeling for biologists

Contact Info

Product

Resources

About

Diverse continuum of CD4⁺T-cell states is determined by hierarchical additive integration of cytokine signals

Diverse continuum of CD4⁺T-cell states is determined by hierarchical additive integration of cytokine signals