ReviewClinical kidney journal2016
Omics databases on kidney disease: where they can be found and how to benefit from them.
Review in Clinical kidney journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Urine Proteomics for Detection of Potential Biomarkers for End-Stage Renal Disease.International journal of molecular sciences · 2025Article
- The Omics-Driven Machine Learning Path to Cost-Effective Precision Medicine in Chronic Kidney Disease.Proteomics · 2025Review
- Multi-scalar data integration decoding risk genes for chronic kidney disease.BMC nephrology · 2024Article
- Pan-Src kinase inhibitor treatment attenuates diabetic kidney injury via inhibition of Fyn kinase-mediated endoplasmic reticulum stress.Experimental & molecular medicine · 2022Article
- Exosomal proteomics in kidney disease: From technical approaches to clinical applications.Journal of food and drug analysis · 2022Review
- Implications of Sphingolipid Metabolites in Kidney Diseases.International journal of molecular sciences · 2022Review
- Emerging Biomarkers for Early Detection of Chronic Kidney Disease.Journal of personalized medicine · 2022Review
- Identification of a foetal epigenetic compartment in adult human kidney.Epigenetics · 2022Article
- Multi-Omics Techniques Make it Possible to Analyze Sepsis-Associated Acute Kidney Injury Comprehensively.Frontiers in immunology · 2022Review
- Big Data in Nephrology.Nature reviews. Nephrology · 2021Review
- Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses.Metabolites · 2021Review
- KF-1607, a Novel Pan Src Kinase Inhibitor, Attenuates Obstruction-Induced Tubulointerstitial Fibrosis in Mice.Biomolecules & therapeutics · 2021Article
- The Use of 'Omics for Diagnosing and Predicting Progression of Chronic Kidney Disease: A Scoping Review.Frontiers in genetics · 2021Article
- Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation.Journal of clinical medicine · 2020Article
- Multi omics analysis of fibrotic kidneys in two mouse models.Scientific data · 2019Article
- Review
- Investigation into the underlying molecular mechanisms of hypertensive nephrosclerosis using bioinformatics analyses.Molecular medicine reports · 2018Article
- Gene, cell, and organ multiplication drives inner ear evolution.Developmental biology · 2017Review
- The systemic nature of CKD.Nature reviews. Nephrology · 2017Review
- Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase.Clinical kidney journal · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.