A two-layer certification framework decouples knowledge validity from human authorship to accommodate AI-enabled research in existing publication systems.
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MIOFlow 2.0 learns stochastic cellular trajectories from transcriptomics data via neural SDEs, unbalanced optimal transport for growth, and a joint latent space unifying gene expression with spatial features.
A stochastic agent-based model integrates tumor and immune cell behaviors to simulate progression and evaluate single and combination cancer therapies.
Cancer shares developmental features with embryos and can be viewed as an evolutionary phenomenon to guide new treatment strategies.
citing papers explorer
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Rethinking Publication: A Certification Framework for AI-Enabled Research
A two-layer certification framework decouples knowledge validity from human authorship to accommodate AI-enabled research in existing publication systems.
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MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data
MIOFlow 2.0 learns stochastic cellular trajectories from transcriptomics data via neural SDEs, unbalanced optimal transport for growth, and a joint latent space unifying gene expression with spatial features.
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A stochastic agent-based model for simulating tumor-immune dynamics and evaluating therapeutic strategies
A stochastic agent-based model integrates tumor and immune cell behaviors to simulate progression and evaluate single and combination cancer therapies.
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Charting an embryological path to cancer cure: A discussion of disease hallmarks
Cancer shares developmental features with embryos and can be viewed as an evolutionary phenomenon to guide new treatment strategies.