ReviewInternational journal of molecular sciences2025
Ovarian Cancer: Multi-Omics Data Integration.
Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- Deep Generative and Graph-Based Representation Learning for Multiomics Survival Stratification in Ovarian Cancer: Secondary Analysis.JMIR bioinformatics and biotechnology · 2026Article
- Protein Variability Patterns in Ovarian Serous Carcinoma.International journal of molecular sciences · 2026Article
- Integration of Multi-Omics Data To Understand the Multifaceted Role of RAMP1 across Different Cancer Types.Cell biochemistry and biophysics · 2026Review
- Transcriptomic and epigenomic insights into ovarian cancer: a bioinformatics perspective - a narrative review.Annals of medicine and surgery (2012) · 2026Article
- Longitudinal deep learning models for tracking disease progression in ovarian cancer using PET/CT imaging and clinical reports.Physical and engineering sciences in medicine · 2026Article
- High-Grade Serous Ovarian Carcinoma in the Genomics Era: Current Applications, Challenges and Future Directions.International journal of molecular sciences · 2026Review
- Integrative bioinformatics approaches for early detection biomarkers in ovarian cancer.Annals of medicine and surgery (2012) · 2026Review
- Advances in multi-omics and aging clock research for female reproductive health and aging.MedScience · 2026Review
- Artificial intelligence (AI) and machine learning (ML) in ovarian cancer: transforming detection, treatment, and prevention.Journal of ovarian research · 2026Review
- Combined analysis of metabolomics and transcriptomics reveals new indicators for the diagnosis and prognosis of colorectal cancer.Contemporary oncology (Poznan, Poland) · 2026Article
- Applications of artificial intelligence and machine learning models in the prognosis and diagnosis of ovarian cancer.Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
This study focuses on the systematization and integration of ovarian cancer multi-omics data, revealing patterns in the application of different omics-based approaches and assessing factors that affect the identification of potential biomarkers. An integrative analysis of 51 publications revealed 1649 potential biomarkers. The findings emphasized the molecular diversity of ovarian cancer. They demonstrated the importance of performing the comprehensive integration of molecular and clinical data to search for diagnostic alternatives and molecular patterns underlying ovarian cancer. The heterogeneity of data sources, differences in data acquisition and analysis protocols, and the lack of uniform standards affect the reproducibility of the results of genomic and post-genomic profiling. Multi-omics studies are more promising than mono-omics-based ones. Despite technological advances, researchers continue to focus on results obtained over a decade ago, which may hinder the scientific community from exploring new horizons in ovarian cancer research.
Indexed as
Identifiers
What Socratic 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 Socratic graph.