Elzbieta Krepska

Executing Multicellular Differentiation: Quantitative Predictive Modelling of C. elegans Vulval Development

MOTIVATION Understanding the processes involved in multi-cellular pattern formation is a central problem of developmental biology, hopefully leading to many new insights, e.g. in the treatment of various diseases. Defining suitable computational techniques for development modelling, able to perform in silico simulation experiments, is an open and challenging problem. RESULTS Previously, we proposed a coarse-grained, quantitative approach based on the basic Petri net formalism, to mimic the behaviour of the biological processes during multicellular differentiation. Here, we apply our modelling approach to the well-studied process of Caenorhabditis elegans vulval development. We show that our model correctly reproduces a large set of in vivo experiments with statistical accuracy. It also generates gene expression time series in accordance with recent biological evidence. Finally, we modelled the role of microRNA mir-61 during vulval development and predict its contribution in stabilizing cell pattern formation.

Proving stabilization of biological systems

We describe an efficient procedure for proving stabilization of biological systems modeled as qualitative networks or genetic regulatory networks. For scalability, our procedure uses modular proof techniques, where state-space exploration is applied only locally to small pieces of the system rather than the entire system as a whole. Our procedure exploits the observation that, in practice, the form of modular proofs can be restricted to a very limited set. For completeness, our technique falls back on a non-compositional counterexample search. Using our new procedure, we have solved a number of challenging published examples, including: a 3-D model of the mammalian epidermis; a model of metabolic networks operating in type-2 diabetes; a model of fate determination of vulval precursor cells in the C. elegans worm; and a model of pair-rule regulation during segmentation in the Drosophila embryo. Our results show many orders of magnitude speedup in cases where previous stabilization proving techniques were known to succeed, and new results in cases where tools had previously failed.

HipG: parallel processing of large-scale graphs

Distributed processing of real-world graphs is challenging due to their size and the inherent irregular structure of graph computations. We present HipG, a distributed framework that facilitates programming parallel graph algorithms by composing the parallel application automatically from the user-defined pieces of sequential work on graph nodes. To make the user code high-level, the framework provides a unified interface to executing methods on local and non-local graph nodes and an abstraction of exclusive execution. The graph computations are managed by logical objects called synchronizers, which we used, for example, to implement distributed divide-and-conquer decomposition into strongly connected components. The code written in HipG is independent of a particular graph representation, to the point that the graph can be created on-the-fly, i.e. by the algorithm that computes on this graph, which we used to implement a distributed model checker. HipG programs are in general short and elegant; they achieve good portability, memory utilization, and performance.

A Service for Reliable Execution of Grid Applications

In grid environments, with the large number of components (both hardware and software) that are involved in application execution, the overall probability that at least one of these components is (temporarily) non-functional is increasing rapidly. In traditional operating systems, such failures are flagged as fatal and the application will be stopped, relying on a re-start after the problem will have been fixed. In a large grid system, this is not a feasible approach as failures happen too frequently while error diagnostics might not be possible at all.

What Can Formal Methods Bring to Systems Biology

This position paper argues that the operational modelling approaches from the formal methods community can be applied fruitfully within the systems biology domain. The results can be complementary to the traditional mathematical descriptive modelling approaches used in systems biology. We discuss one example: a recent Petri net analysis of C. elegans vulval development.

Executing multicellular differentiation

Motivation: Understanding the processes involved in multi-cellular pattern formation is a central problem of developmental biology, hopefully leading to many new insights, e.g., in the treatment of various diseases. Defining suitable computational techniques for development modelling, able to perform in silico simulation experiments, is an open and challenging problem. Results: Previously, we proposed a coarse-grained, quantitative approach based on the basic Petri net formalism, to mimic the behaviour of the biological processes during multicellular differentiation. Here we apply our modelling approach to the well-studied process of C. elegans vulval development. We show that our model correctly reproduces a large set of in vivo experiments with statistical accuracy. It also generates gene expression time series in accordance with recent biological evidence. Finally, we modelled the role of microRNA mir-61 during vulval development and predict its contribution in stabilising cell pattern formation. Contact: feenstra@few.vu.nl