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In this chapter, we give emphasis on the databases, tools, and current methods used for modeling chronic kidney disease (CKD) based on the integration of the molecular features determined by several omic technologies. Merging and integrating large datasets derived from several discovery platforms used in genomics, transcriptomics, proteomics, and metabolomics, presents a huge challenge within the field of bioinformatics and Systems Biology. One of the main hurdles is the lack of uniformization and connectivity between the different types of molecular data; for example, integration of datasets containing genes or proteins with metabolite data is not straightforward as initially we could expect. We focus on the description and application of several database and software resources, such as standalone and web-based tools for network and pathway visualization. We also present successful applications of omics data integration. Finally, a brief case study in CKD will be presented, in which literature data and experimental omics datasets will be used in order to illustrate, in a descriptive stepwise manner, the use of databases and software tools for development of disease models.

Original publication





Book title

Integration of Omics Approaches and Systems Biology for Clinical Applications

Publication Date



327 - 346