Omics databases on kidney disease: where they can be found and how to benefit from them

Theofilos Papadopoulos, Magdalena Krochmal, Katryna Cisek, Marco Fernandes, Holger Husi, Robert Stevens, Jean-Loup Bascands, Joost P. Schanstra, Julie Klein

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)


In the recent decades, the evolution of omics technologies has led to advances in all biological fields, creating a demand for effective storage, management and exchange of rapidly generated data and research discoveries. To address this need, the development of databases of experimental outputs has become a common part of scientific practice in order to serve as knowledge sources and data-sharing platforms, providing information about genes, transcripts, proteins or metabolites. In this review, we present omics databases available currently, with a special focus on their application in kidney research and possibly in clinical practice. Databases are divided into two categories: general databases with a broad information scope and kidney-specific databases distinctively concentrated on kidney pathologies. In research, databases can be used as a rich source of information about pathophysiological mechanisms and molecular targets. In the future, databases will support clinicians with their decisions, providing better and faster diagnoses and setting the direction towards more preventive, personalized medicine. We also provide a test case demonstrating the potential of biological databases in comparing multi-omics datasets and generating new hypotheses to answer a critical and common diagnostic problem in nephrology practice. In the future, employment of databases combined with data integration and data mining should provide powerful insights into unlocking the mysteries of kidney disease, leading to a potential impact on pharmacological intervention and therapeutic disease management.
Original languageEnglish
Pages (from-to)343-352
Number of pages10
JournalClinical Kidney Journal
Issue number3
Publication statusPublished - 1 Jun 2016


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