#24 · Metabolomics

Multimodal frameworks couple spatial, omics and imaging data to model cell states

The dominant thread is joint use of heterogeneous measurement layers within a single computational framework, with spatial and microenvironmental context serving as the organizing element. The senescence preprint applies Ripley's functions and functional data analysis, with senescence-signature scoring, to quantify senescent cells spatially. NicheTrans uses a spatially aware Transformer to translate between omics modalities conditioned on cellular microenvironment. The lung study coregisters mass spectrometry with nonlinear optical imaging through a hierarchical registration network to map metabolic changes across scales. The Cell preview of Li et al. integrates clinical, multi-omics and organ signatures into multi-layer clocks of biological aging. The Alzheimer's disease meta-program screen for drug repurposing is described only briefly in its summary. What is new relative to prior work is the use of spatial and organ-level context as the integrating axis across modalities, rather than fusion of sequence, expression and simulated readouts alone.