Using bioinformatics computational tools, network maps that integrate the complex interactions of genetics and diseases have been developed. The purpose of this review is to introduce the reader to new approaches in understanding disease-gene associations using network maps, with an emphasis on how the human disease network (HDN) map (or diseasome) was constructed. A search was conducted in PubMed using the years 1999-2011 and using key words diseasome, molecular interaction, interactome, protein-protein interaction, and gene. The information reviewed included journal reviews, open source and web-based databases, and open source computational tools. A review of the literature revealed the complexity of molecular, genetic, and protein structures that contribute to cellular function and possible disease, and how network mapping can help the clinician and scientist gain a better understanding of this complexity Using computational tools and databases of genetics, protein interactions, and diseases, scientists have developed a network map of human genes and human diseases referred to as a diseasome. The diseasome is composed of 22 disease classes represented in different colored circular nodes. Lines connecting nodes indicate shared genes among diseases. Thus, the diseasome map provides a colorfully visual display that helps the user conceptualize gene-disease relationships. This review provides an overview of the use of network maps to understand the interrrelationships of genomics and disease. One such map, the diseasome, could be used as a reference for biomedical researchers and multidiscipline health care providers, including nurse practitioners and genetic counselors, to enhance their conceptualization and understanding of the genetic origins of disease.