Dengue fever, a mosquito-borne illness, is prevalent in tropical and subtropical areas worldwide. Patients with dengue fever (DF) or dengue haemorrhagic fever (DHF) usually have common symptoms at the early febrile stage but DHF patients become more severe and lethal over time. Some organizations have taken preventive and palliative measures, but there is still a need for effective treatment. Therefore, it is crucial to study the change in the host’s genetic signature during progression of the disease. This study aims to find stage-specific disease markers for different stages of dengue infection by analysing gene expression of patients with DF and DHF. Initially, a real-life GEO dataset having normal, DF and DHF samples were collected. After analysing genetic patterns in each sample group, three co-expression networks were prepared to understand how genes are expressed together in the same phenotypic condition. Next, the topological dissimilarities across co-expression networks were examined and two differentially co-expressed networks were obtained. Using the hierarchical clustering method, dengue stage-specific markers were identified from the differentially co-expressed networks. Finally, the biological validation study was performed to evident the biological importance of the identified markers. Our application of dengue data showed its potential to offer new insights into other biological issues.