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cs.LG2025
Interpretable Neural ODEs for Gene Regulatory Network Discovery under Perturbations
Zaikang Lin, Sei Chang, Aaron Zweig +4
Modern high-throughput biological datasets containing thousands of perturbations enable large-scale discovery of causal graphs that represent regulatory interactions between genes.…
cs.LG2023★ 3 cited
Causal machine learning for single-cell genomics
Alejandro Tejada-Lapuerta, Paul Bertin, Stefan Bauer +3
Advances in single-cell omics allow for unprecedented insights into the transcription profiles of individual cells. When combined with large-scale perturbation screens, through whi…