Abstract
AbstractSmall over-represented motifs in biological networks are believed to represent essential functional units of biological processes. A natural question is to gauge whether a motif occurs abundantly or rarely in a biological network. Given that high-throughput biotechnology is only able to interrogate a portion of the entire biological network with non-negligible errors, we develop a powerful method to correct link errors in estimating undirected or directed motif counts in the entire network from noisy subnetwork data.KeywordsFalse Negative RateBiological NetworkMissing LinkTranscription Factor NetworkHuman InteractomeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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