The human disease network (diseasome) is a bipartite graph connecting genetic disorders and disease genes, revealing shared genetic origins and functional modules. The study constructs the diseasome using OMIM data, showing that most disorders share genetic links, with cancer being the most connected. The disease gene network (DGN) reveals that disease genes are often in distinct functional modules, with some genes involved in multiple disorders. Essential genes are more likely to be hubs in the interactome, while nonessential disease genes are peripherally located. Analysis shows that nonessential disease genes are not associated with hubs, have less synchronized expression, and are expressed in fewer tissues. Somatic mutations in cancer genes are more likely to affect central modules, supporting the idea that cancer genes are functionally and topologically central. The study highlights the importance of network-based approaches in understanding disease mechanisms and the role of cellular networks in disease development. The findings suggest that most nonessential disease genes occupy peripheral positions in the cellular network, while essential genes are central. The results support the hypothesis that disease genes are functionally related and provide a framework for understanding complex diseases through network analysis.The human disease network (diseasome) is a bipartite graph connecting genetic disorders and disease genes, revealing shared genetic origins and functional modules. The study constructs the diseasome using OMIM data, showing that most disorders share genetic links, with cancer being the most connected. The disease gene network (DGN) reveals that disease genes are often in distinct functional modules, with some genes involved in multiple disorders. Essential genes are more likely to be hubs in the interactome, while nonessential disease genes are peripherally located. Analysis shows that nonessential disease genes are not associated with hubs, have less synchronized expression, and are expressed in fewer tissues. Somatic mutations in cancer genes are more likely to affect central modules, supporting the idea that cancer genes are functionally and topologically central. The study highlights the importance of network-based approaches in understanding disease mechanisms and the role of cellular networks in disease development. The findings suggest that most nonessential disease genes occupy peripheral positions in the cellular network, while essential genes are central. The results support the hypothesis that disease genes are functionally related and provide a framework for understanding complex diseases through network analysis.