ArticleDiscover oncology2025
Progress in ubiquitination and hepatocellular carcinoma: a bibliometric analysis.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in breast ultrasound: a systematic review of research advances.Frontiers in oncology · 2025Pooled it
- Challenges and Opportunities in Cronkhite-Canada Syndrome Research: A Bibliometric Analysis Based on the Web of Science Core Collection.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
- Targeting MED8 enhances sorafenib sensitivity in hepatocellular carcinoma by disrupting epithelial-mesenchymal transition mechanisms.Journal of enzyme inhibition and medicinal chemistry · 2025Article
- Global research trends on the association between gastric cancer and chronic atrophic gastritis: a bibliometric analysis.Discover oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
background and purposeUbiquitination modifications can affect hepatocellular carcinoma (HCC) progression through various signaling pathways. However, no significant results have been observed regarding protein ubiquitination in HCC's therapeutic transformation. This study aimed to explore the research areas related to ubiquitination and HCC from a bibliometric perspective.
methodsArticles and reviews on HCC and ubiquitination published between 2000 and 2023 were obtained from the Web of Science Core Collection (WOSCC). CiteSpace, VOSviewer, and R-bibliometrix were used for the bibliometric and visualization analyses.
resultsAltogether, 358 papers on ubiquitination and HCC were extracted from the WOSCC. Over 24 years, the number of publications has increased. Since the beginning of 2019, studies related to this topic have increased significantly, indicating that the role of ubiquitination modification in HCC is currently popular. China is the leading country in this field with the largest number of publications. The Chinese Academy of Sciences is one of the most influential institutions. Qiao, Yongxia, and Zhang Jie are highly productive authors with major achievements. The journal Cell Death & Disease had the highest number of publications, and the most highly cited journal was Oncogene. The highest citation burst intensity was Sung (2021). In the keyword strategy map, "cancer antigens" are popular keywords in HCC and ubiquitination research.
conclusionA comprehensive visual analysis of ubiquitination and HCC research was conducted using bibliometric methods, showing the publications and popular topics in this field over the past two decades, thus providing references for the future direction of ubiquitination and HCC research.
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.