OmicsLM integrates continuous omics embeddings into LLMs for multi-sample biological reasoning, matching specialized models on profile tasks while outperforming them and general LLMs on language-guided QA over real expression data.
Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq
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Shesha quantifies directional coherence of single-cell CRISPR responses, correlates strongly with effect magnitude, distinguishes pleiotropic from lineage-specific regulators, and predicts chaperone activation after magnitude correction.
Geometric stability, defined as the directional coherence of cellular responses to perturbation, provides a framework for assessing whether resulting cellular states are stable beyond conventional metrics of intervention success.
citing papers explorer
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OmicsLM: A Multimodal Large Language Model for Multi-Sample Omics Reasoning
OmicsLM integrates continuous omics embeddings into LLMs for multi-sample biological reasoning, matching specialized models on profile tasks while outperforming them and general LLMs on language-guided QA over real expression data.
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Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress
Shesha quantifies directional coherence of single-cell CRISPR responses, correlates strongly with effect magnitude, distinguishes pleiotropic from lineage-specific regulators, and predicts chaperone activation after magnitude correction.
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From Syntax to Semantics: Geometric Stability as the Missing Axis of Perturbation Biology
Geometric stability, defined as the directional coherence of cellular responses to perturbation, provides a framework for assessing whether resulting cellular states are stable beyond conventional metrics of intervention success.