Reconstructing Pathways in Large Genetic Networks from Genetic Perturbations

Andreas Wagner

Working Papers from Santa Fe Institute

Abstract: 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.

Keywords: Genomics; reverse engineering; microarrays (search for similar items in EconPapers)
Date: 2001-09
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Persistent link: https://EconPapers.repec.org/RePEc:wop:safiwp:01-09-050

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