摘要: Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription translation. The expression levels are typically measured as mRNA concentration micro-array experiments. In a so-called genetic perturbation experiment, small perturbations applied to equilibrium states changes activity measured. One most important problems systems biology is use these data identify interaction pattern network, especially large scale network. authors develop novel algorithm identifying smallest network that explains experimental data. By construction, our identification able incorporate respect priori knowledge known about structure. A qualitative, encoding whether one gene affects another or not, effect positive negative. method based on convex programming relaxation combinatorially hard problem L0 minimisation. apply proposed subnetwork SOS pathway Escherichia coli, segmentation polarity Drosophila melanogaster, an artificial measuring performance method.