ArticleNucleic acids research2024
cfOmics: a cell-free multi-Omics database for diseases.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed.
- Circulating Cell-free DNA as a biomarker for radiation-induced injury: From mechanistic insights to clinical translation.Cancer metastasis reviews · 2026Review
- DNAviWEB: sequencing-free clinical screening of liquid biopsies.Nucleic acids research · 2026Article
- cfMethDB: A Comprehensive cfDNA Methylation Data Resource for Cancer Biomarkers.Genomics, proteomics & bioinformatics · 2026Article
- Early detection and subtyping of gastric cancer: A cell-free DNA fragmentome-based liquid biopsy method.iScience · 2026Article
- Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.Journal of nanobiotechnology · 2026Review
- Comprehensive review of publicly accessible databases for gastrointestinal cancer and future challenges in database construction.Discover oncology · 2026Review
- exoRBase 3.0: an updated resource for extracellular RNAs from human biofluids.Nucleic acids research · 2026Article
- Liquid biopsy in cancer drug resistance: real-time monitoring, mechanistic insights, and translational applications.Frontiers in immunology · 2026Review
- Proceedings of cell-free noncoding RNA biomarker studies in liquid biopsy.Rheumatology and immunology research · 2025Article
- Response Regarding: Using Machine Learning to Predict Weight Gain in Adults: An Observational Analysis From the All of Us Research Program.The Journal of surgical research · 2025Article
- Cholangiocarcinoma: The era of liquid biopsy.World journal of gastroenterology · 2025Review
- Harnessing ferroptosis for precision oncology: challenges and prospects.BMC biology · 2025Review
- Cell-free nucleic acid fragmentomics: A non-invasive window into cellular epigenomes.Translational oncology · 2024Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Liquid biopsy has emerged as a promising non-invasive approach for detecting, monitoring diseases, and predicting their recurrence. However, the effective utilization of liquid biopsy data to identify reliable biomarkers for various cancers and other diseases requires further exploration. Here, we present cfOmics, a web-accessible database (https://cfomics.ncRNAlab.org/) that integrates comprehensive multi-omics liquid biopsy data, including cfDNA, cfRNA based on next-generation sequencing, and proteome, metabolome based on mass-spectrometry data. As the first multi-omics database in the field, cfOmics encompasses a total of 17 distinct data types and 13 specimen variations across 69 disease conditions, with a collection of 11345 samples. Moreover, cfOmics includes reported potential biomarkers for reference. To facilitate effective analysis and visualization of multi-omics data, cfOmics offers powerful functionalities to its users. These functionalities include browsing, profile visualization, the Integrative Genomic Viewer, and correlation analysis, all centered around genes, microbes, or end-motifs. The primary objective of cfOmics is to assist researchers in the field of liquid biopsy by providing comprehensive multi-omics data. This enables them to explore cell-free data and extract profound insights that can significantly impact disease diagnosis, treatment monitoring, and 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.