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BLOOM supports transcriptomic virtual embryo modeling by bridging temporal sampling gaps, exploring extended developmental trajectories and prioritizing gene-dependent hypotheses for experimental investigation.
Spatial transcriptomics is a rapidly evolving technology that allows for the measurement of gene expression in a spatially resolved manner. However, one technical problem that occurs for many sequencing-based spatial transcriptomics platforms is the presence of mRNA lateral diffusion, where mRNA from one spot can bind...
Spatial transcriptomics (ST) is revolutionizing the study of tumor evolution by enabling spatially resolved copy-number alteration (CNA) analysis. However, evaluating the accuracy and robustness of current single-cell (SC) and ST-specific CNA inference tools remains challenging due to the absence of ground-truth datase...
Large-scale genomic language models (gLMs) hold promise for modeling gene regulation, yet their ability to capture personal gene expression variations remains unresolved. We developed xDecoder, a unified decoding framework that utilizes gLMs and sequence-to-function (S2F) embeddings to learn how personal genetic variat...
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