Inferring network mechanisms: The Drosophila melanogaster protein interaction network

摘要: Naturally occurring networks exhibit quantitative features revealing underlying growth mechanisms. Numerous network mechanisms have recently been proposed to reproduce specific properties such as degree distributions or clustering coefficients. We present a method for inferring the mechanism most accurately capturing given topology, exploiting discriminative tools from machine learning. The Drosophila melanogaster protein is confidently and robustly (to noise training data subsampling) classified duplication–mutation–complementation over preferential attachment, small-world, duplication–mutation without complementation. Systematic classification, rather than statistical study of properties, provides approach understand design complex networks.