ArticleBiomarker research2024
Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation.
Article in Biomarker research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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.
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Who cites it
17 citing papers in PubMed, 22 citations in OpenAlex.
- From cell to disease: Regulatory networks and mechanisms of super‑enhancers in aging (Review).Molecular medicine reports · 2026Review
- Machine learning-driven investigation on liquid-liquid phase separation-related prognostic signature in diffuse large B-cell lymphoma.British journal of haematology · 2026Article
- Phase Separation Drives Pathological Aggregation in Neurodegenerative Diseases: A 15-Year Bibliometric Landscape (2009-2024).Annals of the New York Academy of Sciences · 2026Review
- History and emerging trends of computational fluid dynamics applications in atherosclerosis: a bibliometric analysis and narrative review.Annals of medicine and surgery (2012) · 2026Review
- 3,4-Dimethoxychalcone-induced caloric restriction inhibits PANoptosis to promote ischemic and diabetic skin flap survival: experimental studies.International journal of surgery (London, England) · 2026Article
- Machine Learning in Tuberculosis Research: A Global Bibliometric Analysis of Diagnostic, Prognostic, and Drug Discovery Trends.Therapeutic innovation & regulatory science · 2026Article
- Mapping breast cancer research on monoclonal antibodies: a data-driven approach using VOSviewer, Bibliometrix, and CiteSpace.Naunyn-Schmiedeberg's archives of pharmacology · 2025Article
- Bibliometric and visual analysis of overlooked fatigue in kidney transplantation: a narrative review.Annals of medicine and surgery (2012) · 2025Review
- Data extraction error and its implications on systematic reviews in urology: a protocol.International journal of surgery protocols · 2025Article
- Immune-related adverse events of neoadjuvant immunotherapy in patients with perioperative cancer: a machine-learning-driven, decade-long informatics investigation.Journal for immunotherapy of cancer · 2025Article
- Global research landscape of retinoblastoma biomarkers: a multidisciplinary bibliometric analysis based on multiple databases (2005-2025).Journal of cancer research and clinical oncology · 2025Article
- Multi-omics analysis of bidirectional liquid-liquid phase separation signatures reveals immunotherapy response and prognosis in renal cell carcinoma.BMC cancer · 2025Article
- A Metrology Informatics Investigation of Conversion Therapy in Hepatocellular Carcinoma: 2014-2023.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2025Article
- Article
- Research trends, hotspots and future directions of tertiary lymphoid structures in cancer: a comprehensive informatics analysis and visualization study.Discover oncology · 2024Article
- Artificial intelligence alphafold model for molecular biology and drug discovery: a machine-learning-driven informatics investigation.Molecular cancer · 2024Article
- Therapeutic Efficacy of Quercetin and Its Nanoformulation Both the Mono- or Combination Therapies in the Management of Cancer: An Update with Molecular Mechanisms.Journal of tropical medicine · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R
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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.