Given the topologically central role of nodes in a DS, we hypothesize that a good DS algorithm might capture a set of proteins in a PPI network that are involved in important biological processes and mechanisms crucial for cell vitality, i.e., that DSs of PPI networks might contain BC proteins and signaling pathways (SPs). We test this by constructing a connected dominating set in the human PPI network with an algorithm that is commonly used in telecommunications [57] . We are interested in connected DSs only since signaling pathways are connected. Other algorithms for finding connected DSs are used in telecommunications as well (e.g., [54, 56, 58, 59] ), but are not applicable to biological networks, because they require nodes to be assigned meaningful numerical IDs, e.g., IP addresses in computer networks; clearly, proteins in PPI networks do not have numerically meaningful labels. Also, several algorithms for finding disconnected (i.e., independent; see Methods) DSs exist [60, 61] , but they are inappropriate for our study for the above mentioned reasons. In addition to applying the existing DS algorithm of Rai et al. [57] , we design a new and simpler DS algorithm that outperforms the algorithm of Rai et al. on our data (explained below). Note that the main focus of this study is not to create a state-of-the-art algorithm for finding DSs, but instead, to demonstrate, as a proof of concept, that a DS of a PPI network found by a very simple algorithm indeed captures biologically vital proteins. Any further algorithmic improvements are likely to yield more optimal DSs and hence improve the biological results.