遺伝子相互作用を理解するためにMicroArray データからDAGパターンを発見

抄録

We present in this article a new method to extract frequent patterns from gene networks. The particularity of this method is to be able to extract embedded sub-DAGs from the data, whereas previous methods were limited to extracting induced sub-DAGs. Our algorithm builds up upon our Dryade closed frequent embedded attribute sub-tree mining algorithm, and by postprocessing its outputs discovers closed frequent embedded attribute sub-DAGs with one root in the data. We have tested our method on real gene networks data, and confirmed the existence of specific embedded sub-DAGs, that could not be found with previous algorithms limited to extracting induced sub-DAGs.