ArticleScientific data2025
MLOmics: Cancer Multi-Omics Database for Machine Learning.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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
12 citing papers in PubMed.
- Artificial intelligence empowers targeted protein degradation: Core technological innovations, multi-scenario applications, and translational prospects.Smart molecules : open access · 2026Review
- Worldwide Innovative Network Consortium: Building a Common Global Cancer Database.JCO global oncology · 2026Review
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- Beyond chromatin accessibility: bulk ATAC-seq as an integrative assay to portray genomes and epigenomes.NAR genomics and bioinformatics · 2026Article
- From Spatial Epigenomes to Clinical Diagnostics: Integrative Methylomics Across Scales and Modalities.International journal of molecular sciences · 2026Review
- Unified imputation of missing data modalities and features in multi-omic data via shared representation learning.bioRxiv : the preprint server for biology · 2026Article
- BioLM-NET: an interpretable deep learning model combining prior biological knowledge and contextual LLM gene embeddings on multi-omics data to predict disease.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- CancerSubtypeXplore: A Modular Platform for Multiomics Cancer Subtype Prediction and Biomarker Consensus Discovery.Computational and structural biotechnology journal · 2026Article
- Article
- A statistical physics approach to integrating multi-omics data for disease-module detection.Cell reports methods · 2025Article
- Cancer survival prediction based on soft-label guided contrastive learning and global feature fusion.Bioinformatics (Oxford, England) · 2025Article
- MLOmics: Cancer Multi-Omics Database for Machine Learning.Scientific data · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Framing the investigation of diverse cancers as a machine learning problem has recently shown significant potential in multi-omics analysis and cancer research. Empowering these successful machine learning models are the high-quality training datasets with sufficient data volume and adequate preprocessing. However, while there exist several public data portals, including The Cancer Genome Atlas (TCGA) multi-omics initiative or open-bases such as the LinkedOmics, these databases are not off-the-shelf for existing machine learning models. In this paper, we introduce MLOmics, an open cancer multi-omics database aiming at serving better the development and evaluation of bioinformatics and machine learning models. MLOmics contains 8,314 patient samples covering all 32 cancer types with four omics types, stratified features, and extensive baselines. Complementary support for downstream analysis and bio-knowledge linking are also included to support interdisciplinary analysis.
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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.