Abstract
We present statistical null-models for the structure and the growth of transcription networks, through a data-analysis approach that aims to evaluate feedback and hierarchy in an evolutionary perspective. The analysis is used to establish concrete biological trends, such as whether transcriptional autoregulators have mostly arisen through duplication, or if the existing hierarchical layers of computation are evolutionarily conserved.
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