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Dynamic algorithm for inferring qualitative models of gene regulatory networks
Proceedings. 2004 IEEE Computational Systems Bioinformatics Conference, 2004. CSB 2004.
It is still an open problem to identify functional relations with o(N ·n k ) time for any domain  , where N is the number of learning instances, n is the number of genes (or variables) in the Gene Regulatory Network (GRN) models and k is the indegree of the genes. To solve the problem, we introduce a novel algorithm, DFL (Discrete Function Learning), for reconstructing qualitative models of GRNs from gene expression data in this paper. We analyze its complexity of O(k · N · n 2 ) on thedoi:10.1109/csb.2004.1332448 dblp:conf/csb/YunK04 fatcat:czf5suoiafhpvk6qg54zr3x76i