spEMO: Leveraging Multi-Modal Foundation Models for Analyzing Spatial Multi-Omic and Histopathology Data
Zhao H, Liu T, Huang T, Ding T, Wu H, Humphrey P, Perincheri S, Schalper K, Ying R, Xu H, Zou J, Mahmood F. spEMO: Leveraging Multi-Modal Foundation Models for Analyzing Spatial Multi-Omic and Histopathology Data. 2025 DOI: 10.21203/rs.3.rs-6941589/v1.Peer-Reviewed Original ResearchInformation retrieval capabilitiesMedical report generationMulti-modal alignmentSingle-modal dataDownstream tasksLanguage modelModel architectureComputer systemsAI systemsSpatial domain identificationData modalitiesHistopathological imagesReport generationEvaluation taskMultimodal representationsTaskMulti-omics dataFoundation modelMulti-omics technologiesDataSpatial biologyMulti-OmicsTissue contextDomain identificationInformationscMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links
Wang G, Zhao J, Lin Y, Liu T, Zhao Y, Zhao H. scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links. Nature Communications 2025, 16: 4994. PMID: 40442129, PMCID: PMC12122792, DOI: 10.1038/s41467-025-60333-z.Peer-Reviewed Original ResearchConceptsDeep learning frameworkSingle-cell multi-omics researchSingle-cell multi-omics dataLearning frameworkMulti-omics dataGenerative adversarial networkSingle-cell technologiesData alignmentSingle-cell resolutionMulti-omics researchDownstream analysisCellular statesOmics datasetsAdversarial networkNeural networkProteomic profilingCorrelated featuresBiological informationOmics perspectiveDiverse datasetsFeature topologyDisease mechanismsCell embeddingData resourcesRelationship inference
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