Speaker: Maciej Swat

Abstract:

Virtual-Tissue (VT) simulations are increasingly important tools for understanding how complex multi-scale interactions among biochemical networks, cells, microenvironments, tissues, organs and the whole-body result in normal or disease processes. Understanding cells in the proper spatiotemporal environment is crucial because a cell behavior is a function of its environment.

One of the key issues in VT modeling is the fairly narrow focus of the modeling tools and techniques. Most tools developed to model tissues focus on either tissue mechanics or cell-cell interactions/cell mechanics. Linking to other modeling scales, integration with experimental data, or adding tools/languages for intuitive model constructions are always an afterthought. Because usability issues are simply ignored or, at best, never addressed properly, tools developed to date have a steep learning curve and assume that a motivated modeler will invest the time required to learn the internals of the simulation engine and will develop routines specific for the task at hand on an ad hoc basis. Models generated this way are hard to develop, hard to maintain, analyze, verify and test, are difficult to extend or reuse by others and are rarely used outside an academic setting.

In my talk I will focus on providing possible strategies addressing these issues. I will also present example of how rigorous modeling workflows, implemented in widely used tissue simulation environment (CompuCell3D) led to the construction of the mechanistic model that was used by clinicians to identify key mechanisms responsible for cyst formation in Polycystic Kidney Disease.

About the Speaker:

Dr. Maciej Swat works as a scientist in the Biocomplexity Institute, at Indiana University, Bloomington. He leads CompuCell3D projects (www.compucell3d.org) – a multi-cell, multi-scale Virtual Tissue simulation platform. He has organized multiple workshops focusing on model sharing and the role modeling standards play in facilitating model reuse, reproducibility and cross-validation. His research focuses on building predictive models that help identify defects and abnormalities in cellular behaviors that lead to onset and progression of such tissue diseases as cancer, choroidal neovascularization, diabetic retinopathy or Polycystic Kidney Disease.

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Event Date:

Wednesday, September 9, 2015