Topological effects of data incompleteness of gene regulatory networks

In this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different levels.In doing so, we identify the most relevant factors affecting the validity of previous findings, highlighting important caveats to future prokaryotic TRNs topological analysis.As it is commonly noticed in the literature, gene regulation is a complex process involving different phases and biochemical phenomenologies [1,2]. Among these mechanisms, transcriptional control constitutes one of the main resources the cell relies on to respond biochemically to environmental fluctuations and challenges. As a consequence, systematic characterization of TRNs has turned into a subject of high scientific interest [3]. Topological features of TRNs are customarily characterized at all scales using different metrics. At the large scale, genome-wide TRNs are signed and directed networks which present the following features: (i) regulatory proteins –origin of the regulatory interactions of the whole system– represent a small fraction of the total number of nodes; (ii) out-going connectivity patterns are very heterogeneous –a small percentage of global regulators (hubs) send most of the links; and (iii) in-coming link distributions are quite compact: there is a characteristic scale that defines the typical number of regulations each protein receives [4].Turning to the mesoscale, modularity appears also in TRNs as a key feature to understand the dynamical function of the system. In genome-wide TRNs, each regulator defines its own regulon as the set of nodes directly or indirectly regulated by it. Regulons are then subnetworks, that can be sometimes hierarchically organized; in other occasions, regulons partially overlap in non-trivial ways. Thus, the identification of groups of regulons –or parts of them– interconnected through atypical, dense patterns is expected to stor