Reconstructing pathways in large genetic networks from genetic perturbations.

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. The algorithm's computational complexity is O(nk(2)), where n is the number of genes in the network and k is the average number of genes affected by a genetic perturbation. The algorithm is able to distinguish a large fraction of direct regulatory interactions from indirect interactions, even if the accuracy of its input data is substantially compromised.