 In recent years cell biologists have acquired new tools for studying organization, many of these advanced in systems biology (Green 2017; see the entry on  philosophy of systems and synthetic biology).  One approach in systems biology seeks to develop comprehensive detailed models of the numerous components identified as involved in specific phenomena (Gross &amp; Green 2017). High-throughput data about, for example, which proteins in a cell can bind to each other or which pairs of genes, when mutated together, are lethal, has massively increased the number of cell components associated with any given phenomenon. To make sense of this cell researchers often seek abstract models by constructing networks in which nodes stand for entities and edges for interactions between entities (Green et al. 2018). The challenge researchers face is to make sense of these networks—given the large number of entities involved and their many interactions, these networks can often appear as hairballs. We briefly consider two strategies for analyzing networks in cell biology that philosophers have analyzed.