ORBIT uses an intervention-consistent self-supervised objective in a transformer to infer asymmetric gene program influences from observational scRNA-seq data, recovering Alzheimer's vulnerability patterns and achieving 0.984 macro F1 cell-type classification from 220 pathway scores.
Combinatorial prediction of therapeutic perturbations using causally inspired neural networks
2 Pith papers cite this work, alongside 14 external citations. Polarity classification is still indexing.
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OptimusKG is a labeled property graph unifying biomedical knowledge from structured sources into 190,531 nodes of 10 types and 21.8 million edges of 26 types, with 70% of sampled edges supported by literature evidence via PaperQA3 validation.
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ORBIT: Learning Gene Program Co-Activation Structure for Cell-Type-Stratified Pathway Rewiring Analysis in Single-Cell Transcriptomics
ORBIT uses an intervention-consistent self-supervised objective in a transformer to infer asymmetric gene program influences from observational scRNA-seq data, recovering Alzheimer's vulnerability patterns and achieving 0.984 macro F1 cell-type classification from 220 pathway scores.
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OptimusKG: Unifying biomedical knowledge in a modern multimodal graph
OptimusKG is a labeled property graph unifying biomedical knowledge from structured sources into 190,531 nodes of 10 types and 21.8 million edges of 26 types, with 70% of sampled edges supported by literature evidence via PaperQA3 validation.