ReviewiScience2022
Machine learning for multi-omics data integration in cancer.
Review in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 175 papers, 2 of them syntheses 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
175 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine Learning for Predicting Stroke Risk Stratification Using Multiomics Data: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis.Frontiers in digital health · 2025Pooled it
- Multi-omics graph attention network reveals neuro-immune-tumor pathways in breast cancer liver depression syndrome.Frontiers in immunology · 2026Trial
- A modular framework for antibody-drug conjugate biomarkers.Nature reviews. Clinical oncology · 2026Review
- Integrated Multi-Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- A Systematic Machine Learning Framework for Evaluating and Ranking Omics Layers in Cancer Drug Response Prediction.Current issues in molecular biology · 2026Article
- MicroRNA Dysregulation in HPV-Driven Cervical Cancer: A Review of Oncoprotein-Targeted Signaling Pathways.Life (Basel, Switzerland) · 2026Review
- Genotoxicity of cancer therapies and the risk of secondary malignancies: toward personalized prevention.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Worldwide Innovative Network Consortium: Building a Common Global Cancer Database.JCO global oncology · 2026Review
- EMMA-STRAT: a multi-omics based machine learning framework for stratification of endometrial carcinoma molecular subtypes and MSI status.BioData mining · 2026Article
- Artificial intelligence and oral microbiome: Reshaping the diagnostic and therapeutic paradigm of OSCC.Clinical and translational medicine · 2026Review
- Integrating artificial intelligence and multi-omics data for precision oncology in endometrial cancer: a narrative review.Functional & integrative genomics · 2026Review
- Machine learning-driven QSAR modeling combined with single cell transcriptomics identifies novel drug targets for lung cancer.Journal of translational medicine · 2026Article
- A DNA Methylation Signature Predicts Survival and Platinum Response in HNSCC.Laryngoscope investigative otolaryngology · 2026Article
- KIF23 in disease pathogenesis and its therapeutic and diagnostic potential.Discover oncology · 2026Review
- Integrating multi-omics data for next-generation cancer research and precision medicine.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- From Spatial Epigenomes to Clinical Diagnostics: Integrative Methylomics Across Scales and Modalities.International journal of molecular sciences · 2026Review
- Tissue-specific transfer learning improves functional variant and therapeutic target discoveries in breast and prostate cancer.PLoS genetics · 2026Article
- Article
- Beyond silencing: integrative multi-omics and spatial profiling unravel the systems-level role of piRNAs in HBV-driven Hepatocarcinogenesis.Molecular biology reports · 2026Review
115 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multi-omics data analysis is an important aspect of cancer molecular biology studies and has led to ground-breaking discoveries. Many efforts have been made to develop machine learning methods that automatically integrate omics data. Here, we review machine learning tools categorized as either general-purpose or task-specific, covering both supervised and unsupervised learning for integrative analysis of multi-omics data. We benchmark the performance of five machine learning approaches using data from the Cancer Cell Line Encyclopedia, reporting accuracy on cancer type classification and mean absolute error on drug response prediction, and evaluating runtime efficiency. This review provides recommendations to researchers regarding suitable machine learning method selection for their specific applications. It should also promote the development of novel machine learning methodologies for data integration, which will be essential for drug discovery, clinical trial design, and personalized treatments.
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.