ArticleGenome biology2024
TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology.
Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 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.
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Who cites it
33 citing papers in PubMed.
- TMO-Net+: An Enhanced Tumor Multi-Omics Pre-Trained Network for Multi-Task Learning in Oncology.Genes · 2026Article
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Review
- Article
- Benchmarking computational methods for multi-omics biomarker discovery in cancer.Briefings in bioinformatics · 2026Article
- Identification of immunogenic cell death-related prognostic genes in gastric cancer.Journal of gastrointestinal oncology · 2026Article
- M-GNN: A Topology-Enhanced Multi-Modal Graph Neural Network for Cancer Driver Gene Prediction.Metabolites · 2026Article
- Artificial intelligence models: transforming early diagnosis and precise treatment of gastrointestinal cancers.Molecular cancer · 2026Review
- Mechanical cues as immunomodulators in neuroinflammation-driven spinal sensitization: analgesic mechanisms and therapeutic strategies.Frontiers in immunology · 2026Review
- Artificial intelligence in bioinformatics: a survey.Briefings in bioinformatics · 2025Review
- Transformative advances in single-cell omics: a comprehensive review of foundation models, multimodal integration and computational ecosystems.Journal of translational medicine · 2025Review
- Cancer survival prediction based on soft-label guided contrastive learning and global feature fusion.Bioinformatics (Oxford, England) · 2025Article
- Advancing prognostic and therapeutic prediction in lung squamous cell carcinoma through integrated multi-omics analysis and 117 machine learning combinations.Journal of thoracic disease · 2025Article
- Spatial omics technology potentially promotes the progress of tumor immunotherapy.British journal of cancer · 2025Review
- A Multi-Layered Framework for Modeling Human Biology: From Basic AI Agents to a Full-Body AI Agent.ArXiv · 2025Article
- DeepHVI: A multimodal deep learning framework for predicting human-virus protein-protein interactions using protein language models.Biosafety and health · 2025Article
- Novel cancer subtyping method guided by tumor-normal sample in latent space of transcriptomic variational autoencoder.Scientific reports · 2025Article
- Pan-cancer analysis shapes the understanding of cancer biology and medicine.Cancer communications (London, England) · 2025Review
- PTMFusionNet: A Deep Learning Approach for Predicting Disease Related Post-translational Modification and Classifying Disease Subtypes.Molecular & cellular proteomics : MCP · 2025Article
- Revolutionizing gastroenterology and hepatology with artificial intelligence: From precision diagnosis to equitable healthcare through interdisciplinary practice.World journal of gastroenterology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Cancer is a complex disease composing systemic alterations in multiple scales. In this study, we develop the Tumor Multi-Omics pre-trained Network (TMO-Net) that integrates multi-omics pan-cancer datasets for model pre-training, facilitating cross-omics interactions and enabling joint representation learning and incomplete omics inference. This model enhances multi-omics sample representation and empowers various downstream oncology tasks with incomplete multi-omics datasets. By employing interpretable learning, we characterize the contributions of distinct omics features to clinical outcomes. The TMO-Net model serves as a versatile framework for cross-modal multi-omics learning in oncology, paving the way for tumor omics-specific foundation models.
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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.