Understanding how cells orchestrate their behavior to construct a complex functional organ or an entire organism is an important scientific problem, which despite the tremendous progress in molecular and cell biology poses many open questions (e.g., how are stem cell population dynamics regulated to build and maintain organs.) Computational methods and modelling are beginning to play an important role in understanding developmental processes, by allowing the construction of mechanistic models of the underlying systems, performing in-silico experiments and suggesting new directions for experimental investigation. However, many of the existing computational methods and tools are not accessible to experimental biologists (e.g., large sets of differential equations or complex software code), thus it is difficult for the experts in the field to ensure the hypotheses and assumptions incorporated in the model are reasonable, and that models keep up to date with the latest experimental findings.

To alleviate this problem, we have developed Biocharts, a tool supporting a visual language to model complex dynamics, in an intuitive and more accessible way for the wider scientific community. Biological assumptions and experimental results can be encoded within a common framework, using scenarios and states. Models can be interactively explored by the user to ensure they capture the intended behaviour, visualizing model execution using the same language the model is developed in. We are currently applying the tool in developmental biology and stem cell research.

Biocharts features:

  • Specify intra-cellular and inter-cellular behavior using scenarios and states
  • Use a visual language to build the model and interactively simulate dynamics
  • Represent hypotheses and experimental results within the same framework



Download Biocharts.


The following modeling examples are described in more detail in our documentation

Case studies

  • Stem Cell Population Dynamics in the C. elegans germline (In collaboration with Hubbard lab, New York University).

    We are studying the dynamics of the stem cell population in the C. elegans germline. The dynamics of self-renewing stem cell populations is difficult to understand not only due to an incomplete picture of cellular and molecular processes involved, but also due to the integration of multiple influences such as anatomical constraints, cell-cell communication, and cell division itself. C. elegans is a powerful system to study the underlying principles of stem cell behaviour, see this review to learn more about the system and recent paper and tool examples to learn about the modeling.
  • Bacterial Population Dynamics (In collaboration with Harel lab, Weizmann Institute)

    We are studying bacterial population dynamics using a novel model that integrates chemotaxis pathway, motor activation, metabolism and cell division, aspects that are often modeled in isolation, into a coherent system level model. For more information see this paper and tool examples.
  • Cell Fate Specification

    A central question in developmental biology is how cells acquire specific fates. In many systems there are various processes that are crucial for this developmental event but that are hard to integrate using existing modeling methodologies. We have studied vulval precursor cell fate specification in C. elegans, a “classical” system that demonstrates how within an equivalence group (a group of cells that shares the same developmental potential) cells “compute” and decide which fate to specify, see this paper and additional examples of fate specification including pancreatic cell specification in the tool examples.
  • The making of an organism (In collaboration with Bao lab, Sloan-Kettering)

    A central question in biology is how the information stored in the fertilized egg orchestrates the making of an organism. We have started using our tool to model this process in C. elegans, where the adult worm consists of 959 somatic cells that arise via an invariant cell lineage, see tool examples for initial and simplified modeling of the lineage.

     For more biological examples download the tool and related documentation.

Related publications



Former Interns that have done research related to the tool and methodology: Chris McEwan, Aleks Milicevic, Antti Larjo, Itai Segall.

Biocharts uses Dynamic Data Display for visualising simulation plots and spatial behavior.

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