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Reconstruction Algorithms for Biological Networks

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Improving biological network models

A recent project has developed mathematical models to reconstruct biological networks such as those used to understand cell biology and evolution.

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Mathematical models of networks are increasingly important in biology research. Complex network dynamics define many biological systems, such as ecosystems, co-evolution of species, and molecular networks in plants and animals. The EU-funded 'Reconstruction algorithms for biological networks' (BIONETRECON) project aimed to build and test algorithms to assist scientists in reconstructing these biological networks. This is particularly useful for reconstructing evolutionary trees (called phylogenies), and interrelatedness between populations of a single species (pedigrees). Project work first focused on ways to improve reconstruction of phylogenetic trees. Researchers made progress in more accurately defining the assumptions required to reconstruct these trees, thus improving the accuracy of said reconstruction. Other BIONETRECON work proved that two long-held assumptions regarding phylogenetics are contradictory. The project also made progress in improving the accuracy of the Markov Chain Monte Carlo model, a common method used for phylogenetic reconstruction. BIONETRECON has made important contributions in terms of improving the understanding and accuracy of biological network reconstruction.


Biological network, biological network models, mathematical models, biological networks, cell biology, evolution, reconstruction algorithms, phylogenies, phylogenetic reconstruction

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