ArticleOncotarget2018
Parenclitic networks for predicting ovarian cancer.
Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-Derived Blood Biomarkers for Ovarian Cancer Diagnosis: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Parenclitic network mapping predicts survival in critically ill patients with sepsis.Physiological reports · 2025Article
- Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer.Scientific reports · 2023Article
- Maternal PlGF and umbilical Dopplers predict pregnancy outcomes at diagnosis of early-onset fetal growth restriction.The Journal of clinical investigation · 2023Article
- A proteomic survival predictor for COVID-19 patients in intensive care.PLOS digital health · 2022Article
- Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance.European radiology · 2022Article
- Prognosis and Survival Modelling in Cirrhosis Using Parenclitic Networks.Frontiers in network physiology · 2022Article
- Parenclitic and Synolytic Networks Revisited.Frontiers in genetics · 2021Article
- The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort.PloS one · 2021Article
- Multi-Marker Longitudinal Algorithms Incorporating HE4 and CA125 in Ovarian Cancer Screening of Postmenopausal Women.Cancers · 2020Article
- The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging.Frontiers in aging neuroscience · 2020Article
- Comparison of Human Epididymis Protein 4, Cancer Antigen 125, and Ultrasound Prediction Model in Differentiating Benign from Malignant Adnexal Masses.Journal of mid-life healthArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Prediction and diagnosis of complex disease may not always be possible with a small number of biomarkers. Modern 'omics' technologies make it possible to cheaply and quantitatively assay hundreds of molecules generating large amounts of data from individual samples. In this study, we describe a parenclitic network-based approach to disease classification using a synthetic data set modelled on data from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) and serological assay data from a nested set of samples from the same study. This approach allows us to integrate quantitative proteomic and categorical metadata into a single network, and then use network topologies to construct logistic regression models for disease classification. In this study of ovarian cancer, comprising of 30 controls and cases with samples taken <14 months to diagnosis (
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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.