Multi-Omics Data Integration

Latest papers

17 papers2 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

ARO: Aligned Representation learning for multi-Omics data
Oct 5, 2026Amogh Singh, Yash Shah, Chiara D'Ercoli +4Missing-Modality Learning Learning with Missing Data
Department of Computer Science, University of Cambridge, Cambridge, UK · DIAG, University of Rome “Sapienza”, Rome, Italy · Max Planck Institute for Intelligent Systems
Evaluating Single and Multi-Omics Based Explainable Artificial Intelligence (MOXAI) for Molecular Subclass Classification of Adult-Type Diffuse Gliomas
Sep 26, 2026Md Zahangir Alom, Quynh T. Tran, Breuer Alexandar +1Multi-Omics Data Integration Brain Tumor Classification
Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN 38105 USA.
OmicSync: Reliability-Aware Spatial Multi-Omics Clustering with Evidence-Constrained LLM Reasoning
Aug 24, 2026Rabeya Tus Sadia, Qiang Ye, Qiang ChengClustering Multi-Omics Data Integration
Department of Computer Science, University of Kentucky · Department of Mathematics, University of Kentucky
Learning latent progression states from spatial heterogeneity in uterine histopathology
Aug 18, 2026Qiming He, Yan Liu, Shuang Ge +20Multi-Omics Data Integration Computational Pathology
Fuzhou University Affiliated Provincial Hospital, Interdisciplinary Institute for Medical Engineering, Fuzhou University, Fuzhou, China
Diagonal Multi-omics Integration of Heterogeneous Datasets
Aug 17, 2026Maksim V. Kukushkin, Mikhail S. Arbatskiy, Dmitriy E. Balandin +1Multi-Omics Data Integration
Pirogov Russian National Research Medical University, Russian Clinical and Research Center of Gerontology, Ministry of Health of the Russian Federation, 129226, Moscow, Russia · Russian Academy of Sciences, Kabardino-Balkarian Scientific Center, Institute of Applied Mathematics and Automation, 360000, Nalchik, Russia
DoGMA: A Central-Dogma-Guided Foundation Model for Multi-Omics Alignment and Multi-Task Learning in Oncology
Aug 8, 2026Junfei Ling, Bangzheng Pu, Bingsen Xue +3Cancer Survival Prediction Clinical Outcome Prediction
Institute of Medical Robotics, Shanghai Jiao Tong University · Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China · Institute of Data Science, The University of Hong Kong +1
Adaptive Confidence-weighted Expansion for Trustworthy Multi-Omics Multimodal Fusion
Jul 22, 2026Mohammad Raahemi, Ali Sekhavati, Alireza Maleki +1Probability Calibration Uncertainty Quantification
Faculty of Engineering, University of Ottawa, Ottawa ON K1N 1A2, Canada · RIV Lab, Department of Computer Engineering, Bu-Ali Sina University, Hamedan, Iran · School of Computing and Communications, Lancaster University, Lancaster, UK
LATTICE: Graph Self-Supervised Learning for Multimodal Spatial Omics Integration
Jul 15, 2026Jagan Mohan Reddy Dwarampudi, Veena Kochat, Suresh Satpati +2Spatial Transcriptomics Graph SSL
University of Houston · MD Anderson Cancer Center
Biologically Informed Deep Neural Networks for Multi-Omic Integration, Pathway Activity Inference and Risk Stratification in Cancer
Jul 6, 2026Pedro Henrique da Costa Avelar, Le Ou-Yang, Min Wu +1Cancer Survival Prediction Autoencoders
Department of Informatics, King’s College London, London WC2B 4BG, United Kingdom · Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore 138632, Singapore · Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester +1
HERO: Hypothesis-Driven Evidence Retrieval from Omics for Multi-Task Breast Cancer Analysis
Jun 19, 2026Xiangyu Li, Ran SuBreast Cancer Clinical Outcome Prediction
College of Intelligence and Computing, Tianjin University, Tianjin 300072, China
Latent World Recovery for Multimodal Learning with Missing Modalities
Jun 10, 2026Hui Wang, Tianyu Ren, Joseph Butler +3Missing-Modality Learning Cross-Modal Alignment
Queen’s University Belfast, Belfast, United Kingdom
SDM-Q: Cost-Aware Staged Decision-Making for Multi-Omics Classification with Deep Q-Learning
May 29, 2026Nan Mu, Yangfan Xiao, Ling Wang +3Cost-Sensitive Learning Deep Q-Learning
College of Computer Science, Sichuan Normal University, Chengdu, Sichuan 610101, China. · Department of Mathematics, College of Science and Mathematics, Kennesaw State University, Kennesaw, GA 30144, USA. · Department of Computer Science, College of Computing and Software Engineering, Kennesaw State University, Marietta, GA 30060, USA.
CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation
Apr 30, 2026Andac Demir, Erik W. Anderson, Jeremy L. Jenkins +1Single-Cell Perturbation Modeling Genomics
Novartis Biomedical Research
PathMoG: A Pathway-Centric Modular Graph Neural Network for Multi-Omics Survival Prediction
Apr 27, 2026Di Wang, Chupei Tang, Junxiao Kong +3Survival Analysis Graph Neural Networks
1Cuiying Honors College, Lanzhou University, China · School of Mathematics and Statistics, Lanzhou University, China · School of Mathematics and Statistics, Lanzhou University, China and Shanghai Innovation Institute +1
CMGL: Confidence-guided Multi-omics Graph Learning for Cancer Subtype Classification
Apr 27, 2026Boyang Fan, Hengchuang Yin, Siyu Yi +5Oncology Cancer Subtype Classification
College of Computer Science, Sichuan University, Chengdu, China · Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China · College of Mathematics, Sichuan University, Chengdu, China +1
Genetic algorithms for multi-omic feature selection: a comparative study in cancer survival analysis
Mar 31, 2026Luca Cattelani, Vittorio FortinoFeature Selection Genetic Algorithms
Institute of Biomedicine, School of Medicine, University of Eastern Finland, Yliopistonranta 8, 70210, Finland
DeepDTF: Dual-Branch Transformer Fusion for Multi-Omics Anticancer Drug Response Prediction
Mar 25, 2026Yuhan Zhao, Jacob Tennant, James Yang +3Multi-Omics Data Integration Cancer Drug Response Prediction
Department of Computer Science, North Carolina State University, Raleigh, NC, USA · UNC School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA · Department of Molecular and Structural Biochemistry, North Carolina State University, Raleigh, NC, USA

Oct 5, 2026J/K move · Enter open · S save

ARO: Aligned Representation learning for multi-Omics data

Amogh Singh, Yash Shah, Chiara D'Ercoli, Arash Mehrjou+3

Department of Computer Science, University of Cambridge, Cambridge, UK · DIAG, University of Rome “Sapienza”, Rome, Italy · Max Planck Institute for Intelligent Systems

Missing-Modality Learning Learning with Missing Data Multi-Omics Data Integration Molecular Representation Learning

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The high cost of functional molecular assays, and prevalence of missing modalities and unmatched samples in computational biology, create significant barriers to comprehensive multi-omic profiling, essential for capturing and reasoning over molecules, cells, tissues, and organisms. This work proposes a model that learns meaningful representations from multi-omics cancer data supporting the reconstruction of missing and unpaired modalities. Contrary to increasingly complex, larger models, e.g. Foundation Models (FMs), ARO prioritizes practical applicability in limited or incomplete data settings. ARO optimally reconstructs missing modalities (MSE of

0.15

on the validation and test data in the Unmasked settings), with its learned latent embeddings enabling a downstream cancer classification task. Our findings indicate that analyzing diverse molecular layers as a single integrated system offers a reliable and cost-efficient approach, reducing dependence on large-scale experimental testing, while still supporting multi-omic exploration in limited data settings.