I present an algorithm that determines the longest path between every gene pair in an arbitrarily large genetic network from large scale gene perturbation data. As a by-product, the algorithm reconstructs all direct regulatory gene interactions in the network. The algorithm is recursive, and is built around a graph representation of genetic networks. Its computational complexity is O(nk2), where n is the number of genes in the network, and k is the average number of genes affected by a genetic perturbation. In practice, it can reconstruct all path lengths for a network of more than 6000 genes in less than 30 CPU seconds. It is able to distinguish a large fraction of direct regulatory interactions from indirect interactions, even if the quality of its input data is substantially compromised.
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Paper provided by Santa Fe Institute in its series Working Papers with number
01-09-050.