GNW Java tool for generating realistic in silico benchmarks for gene network algorithms
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Java tool for generating realistic in silico benchmarks for gene network algorithms GeneNetWeaver (GNW) is an easy-to-use Java tool for generating realistic in silico benchmarks for gene network reverse engineering algorithms. GNW was used to generate the DREAM3 In Silico Challenges.It is well known that the performance of reverse engineering methods can be very sensitive to the type of network structure that they are applied to (e.g., a method may perform well on Erdös-Rény networks and fail on scale-free networks). Thus, for a fair comparison of methods, it's crucial that the benchmark networks have a realistic structure.Instead of using random graph models, which are known to only partially capture the structural properties of biological networks, we generate network structures by extracting modules from known biological interaction networks. In ref. After generating realistic network structures, the next question is how to generate realistic data from these networks using adequate dynamical models. In previous in silico benchmarks (e.g., Mendes et al.), relatively simple phenomenological models were used for this purpose. Requirements: · Java

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