The relevance of topology in parallel simulation of biological networks

Tommaso Mazza, Paolo Ballarini, Rosita Guido, Davide Prandi

Research output: Contribution to journalArticlepeer-review

Abstract

Important achievements in traditional biology have deepened the knowledge about living systems leading to an extensive identification of parts-list of the cell as well as of the interactions among biochemical species responsible for cell's regulation. Such an expanding knowledge also introduces new issues. For example, the increasing comprehension of the interdependencies between pathways (pathways cross-talk) has resulted, on one hand, in the growth of informational complexity, on the other, in a strong lack of information coherence. The overall grand challenge remains unchanged: to be able to assemble the knowledge of every "piece of a system in order to figure out the behavior of the whole (integrative approach). In light of these considerations, high performance computing plays a fundamental role in the context of in-silico biology. Stochastic simulation is a renowned analysis tool, which, although widely used, is subject to stringent computational requirements, in particular when dealing with heterogeneous and high dimensional systems. Here, we introduce and discuss a methodology aimed at alleviating the burden of simulating complex biological networks. Such a method, which springs from graph theory, is based on the principle of fragmenting the computational space of a simulation trace and delegating the computation of fragments to a number of parallel processes.

Original languageEnglish
Article number6143919
Pages (from-to)911-923
Number of pages13
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume9
Issue number3
DOIs
Publication statusPublished - 2012

Keywords

  • Graphs and network
  • Parallel computing
  • Stochastic simulation
  • Systems biology

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

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