FMMB 2014: First International Conference on Formal Methods in Macro-Biology

Over the past decade, formal methods from computer science have been successfully applied in life sciences to decipher biological processes mostly at the molecular and cellular levels. Extending these methods to higher levels in systems biology, such as tissues, organs, but also populations and ecosystems is a challenging issue. In order to analyze such complex systems, temporal and spatial models able to represent a large number of components acting at dierent scales are required. Beyond ordinary and partial dierential equation systems, powerful modeling languages, approximation techniques and effcient algorithms need be designed, by involving experts from dierent disciplines, for tackling challenging macro biology questions.

The purpose of FMMB is to bring together researchers, developers, and students in theoretical computer science, applied mathematics, mathematical and computational biology, interested in studying the application of formal methods to the construction and analysis of models describing biological processes at both micro and macro levels.

The topics of interest include (but are not limited to):

  • representation and analysis of biological systems in formal systems such as:
    • ordinary and partial differential equation systems,
    • discrete event systems, infinite state systems,
    • hybrid discrete-continuous systems, hybrid automata,
    • cellular automata, multi-agent systems,
    • stochastic processes, stochastic games,
    • statistical physics models,
    • process algebras, process calculi,
    • rewriting systems, graph grammars,
  • coupling models and data, inference of models from data,
  • computability and complexity issues,
  • modelling and analysis tools, case studies.

Application areas particularly solicited include:

  • environmental biology, ecology, marine science,
  • agriculture and forestry,
  • developmental biology, population biology,
  • epidemiology, medicine,
  • systems biology, synthetic biology.
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