Phosphorylation-based signalling implicates a complex and intertwined ensemble of pathways that is critical to all domains of life. The interconnectivity between pathways results in the emergence of complex networks whose elucidation present a serious challenge. Many phosphorylation interactions that occur in human cells have been identified and constitute the basis for the known phosphorylation interaction network. In most traditional phosphorylation studies, a single phosphorylation interaction, or a single pathway, are interrogated. Though this is an effective strategy to address specific questions, it fails to reflect the complexity and size of the phosphorylation network within eukaryotic cells. In our system-wide approach, we use antibody microarrays to comprehensively identify changes in host cell phosphorylation networks following infection. To analyse the large datasets produced by these arrays, we have developed a pathway analysis tool that we called MAPPINGS (Mapping and Analysis of Phosphorylation Pathways Identified through Network/Graph Signalling). The program uses random walks based on the aforementioned known phosphorylation network to identify chains of phosphorylation events occurring much more or much less frequently than expected. MAPPINGS highlights pathways of phosphorylation that work synergistically, providing a rapid interpretation of the most critical pathways following infection. In our initial construction of the program, we interrogated the host erythrocyte’s response to infection with the malaria parasite Plasmodium falciparum. This enabled us to confirm a number of previously described host phosphorylation events and, importantly, to identify several additional phosphorylation events and to suggest pathways in which such events are involved. The analysis strategy described here is widely applicable to comparative phosphorylation datasets in any context (e.g. response of cells to infection, treatment, or comparison between differentiation stages of any cell populations) and provides a rapid and reliable analysis to guide validation studies, which can reduce dataset analysis time dramatically.