Frequent Pattern Discovery in Multiple Biological Networks: Patterns and Algorithms
نویسندگان
چکیده
The rapid accumulation of biological network data is creating an urgent need for computational methods capable of integrative network analysis. This paper discusses a suite of algorithms that we have developed to discover biologically significant patterns that appear frequently in multiple biological networks: coherent dense subgraphs, frequent dense vertex-sets, generic frequent subgraphs, differential subgraphs, and recurrent heavy subgraphs. We demonstrate these methods on gene co-expression networks, using the identified patterns to systematically annotate gene functions, map genome to phenome, and perform high-order cooperativity analysis.
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