ArticleScientific reports2017
Establishment of a integrative multi-omics expression database CKDdb in the context of chronic kidney disease (CKD).
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
15 citing papers in PubMed, 28 citations in OpenAlex.
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Network-based analyses of multiomics data in biomedicine.BioData mining · 2025Review
- Identification of mechanistic CKD biomarkers in a rat SNx kidney fibrosis model by transcriptomics and proteomics detectable in biofluids.Scientific reports · 2025Article
- Rewiring Drug Research and Development through Human Data-Driven Discovery (HDPharmaceutics · 2023Review
- Big Data in Nephrology.Nature reviews. Nephrology · 2021Review
- Chronic Kidney Disease Cohort Studies: A Guide to Metabolome Analyses.Metabolites · 2021Review
- A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation.Frontiers in molecular neuroscience · 2021Article
- Urinary Peptidomic Biomarkers in Kidney Diseases.International journal of molecular sciences · 2019Review
- Article
- The metabolomic quest for a biomarker in chronic kidney disease.Clinical kidney journal · 2018Article
- Proteomic Profiling Reveals the Transglutaminase-2 Externalization Pathway in Kidneys after Unilateral Ureteric Obstruction.Journal of the American Society of Nephrology : JASN · 2018Article
- C/VDdb: A multi-omics expression profiling database for a knowledge-driven approach in cardiovascular disease (CVD).PloS one · 2018Article
- Inflammation-Related Mechanisms in Chronic Kidney Disease Prediction, Progression, and Outcome.Journal of immunology research · 2018Review
- Renal biopsy-driven molecular target identification in glomerular disease.Pflugers Archiv : European journal of physiology · 2017Review
- Drugs and Targets in Fibrosis.Frontiers in pharmacology · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Complex human traits such as chronic kidney disease (CKD) are a major health and financial burden in modern societies. Currently, the description of the CKD onset and progression at the molecular level is still not fully understood. Meanwhile, the prolific use of high-throughput omic technologies in disease biomarker discovery studies yielded a vast amount of disjointed data that cannot be easily collated. Therefore, we aimed to develop a molecule-centric database featuring CKD-related experiments from available literature publications. We established the Chronic Kidney Disease database CKDdb, an integrated and clustered information resource that covers multi-omic studies (microRNAs, genomics, peptidomics, proteomics and metabolomics) of CKD and related disorders by performing literature data mining and manual curation. The CKDdb database contains differential expression data from 49395 molecule entries (redundant), of which 16885 are unique molecules (non-redundant) from 377 manually curated studies of 230 publications. This database was intentionally built to allow disease pathway analysis through a systems approach in order to yield biological meaning by integrating all existing information and therefore has the potential to unravel and gain an in-depth understanding of the key molecular events that modulate CKD pathogenesis.
Indexed as
Identifiers
What OpenQuestion holds
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.