Estimating Coarse Gene Network Structure from Large-Scale Gene Perturbation Data

Andreas Wagner

Working Papers from Santa Fe Institute

Abstract: Large scale gene perturbation experiments generate information about the number of genes whose activity is directly or indirectly affected by a gene perturbation. From this information, one can numerically estimate coarse structural network features such as the total number of direct regulatory interactions and the number of isolated subnetworks in a transcriptional regulation network. Applied to the results of a large-scale gene knockout experiment in the yeast Saccharomyces cerevisiae, the results suggests that the yeast transcriptional regulatory network is very sparse, containing no more direct regulatory interactions than genes. The network comprises more than one hundred independent sub-networks.

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:01-09-051

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