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Executable Modeling of Morphogenesis : A Turing-Inspired Approach

Setty Y., Cohen I.R., Harel D.

Fundamenta Informaticae

2012

Vol. 118, nr 4

403-417

In his pioneering 1952 paper, ”The chemical basis of morphogenesis”, Alan Turing introduced, perhaps for the first time, a model of the morphogenesis of embryo development. Central to his theory is the concept of cells with chemical entities that interact with morphogens to drive embryonic development through changes in what he termed ’the state of the system’. Turing’s concepts have inspired many mathematical and computational models proposed since then. Here we discuss the way Turing’s ideas inspired our approach to the state-based modeling of morphogenesis, which results in a fully executable program for the interactions between chemical entities and morphogens. As a representative example we describe our modeling of pancreatic organogenesis, a complex developmental process that develops from a flat sheet of cells into a 3D cauliflower-like shape. We show how we constructed the model and tested the relations between morphogens and cells, and illustrate the analysis of the model against experimental data. Finally, we discuss a variant of the original Turing-Test for a machine’s ability to demonstrate intelligence as a future means to validate computerized biological models, like the one presented here.

Modeling Biology using Generic Reactive Animation

Setty Y., Cohen I.R., Harel D.

Fundamenta Informaticae

2010

Vol. 103, nr 1-4

235-246

Complex biological systems involve incorporated behaviors of numerous processes, mechanisms and objects. However, experimental analysis, by its nature, divides biological systems into static interactions with little dynamics. To bridge the gap between experimental data and the underlying behavior, our group has been formalizing biological findings into mathematically and algorithmically rigorous specifications, which are then compiled into reactive models. To realistically animate our models, we designed a generic architecture for the earlier idea of reactive animation, in a way that allows it to link up reactive models with animation tools. Here, we describe the reactive animation approach and some of the benefits of employing it to simulate and analyze complex biological systems. We illustrate our approach with a model of pancreatic development, a highly complex system with a unique 3D structure, and also mention more recent work on adding animation to the generic cell project (GemCell).