To varying degrees, we find that many of these pathway proteins show preferential association with these checkpoint-inducing DNA structures. We also find that the ionic strength of the binding reaction can significantly impact checkpoint protein-DNA interactions. Furthermore, we find that under mildly stringent binding conditions, the checkpoint mediator proteins Claspin and Tipin show the greatest ability to discriminate checkpoint-inducing DNA structures from undamaged, double-stranded DNA. We therefore conclude that robust activation of DNA damage checkpoint responses by branched DNA structures and bulky DNA adducts may depend, in part, on the formation of multiple, cooperative checkpoint protein-DNA interactions. Though the direct contact of ATRIP with RPA stabilizes ATRIP on RPA-coated ssDNA in vitro and aids its recruitment to immunofluorescently-defined foci in vivo, ATRIP can also directly bind to DNA in the absence of RPA. Our finding that ATRIP showed an increased affinity for the branched DNA structure in comparison to either ssDNA or dsDNA indicates that ATRIP has the potential to directly sense stalled replication forks in vivo in the absence of other factors, including RPA. XPA has previously been shown to bind branched DNA structures, which may be relevant to its coordination of the incision events during nucleotide excision repair. Though XPA directly binds ATR and is required for optimal UV-induced phosphorylation of Chk1, there is currently no evidence that the association of XPA with branched DNA structures is relevant to ATR-Chk1 signaling. These results highlight the fact that only limited conclusions can be drawn from protein-DNA interaction data in the absence of other relevant, biological evidence. Interestingly, Claspin, the Timeless-Tipin complex, and Timeless and Tipin individually all showed preferential association with the branched DNA.The interplay of differentially expressed signaling molecules was examined in more detail by network analysis. ExPlain generated the network clusters in a data driven process, which is guided by the specified input set of molecules. The resulting clusters represent context-specific subdistricts of the entire cellular network, which are densely populated with molecules targeted by observed expression changes. The network clusters constructed for upregulated transgenic and tumor molecules connected components of growth factor signaling, cell cycle regulation, as well as chemokine and cytokine signaling. We assume that the interplay of molecules with different canonical functions provides for a realistic view on cellular control mechanisms. These are implemented by a cellular network that connects thousands of molecules, many of which exert a regulatory role in a multiplicity of biological contexts.