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Found 2 papers, 2 papers with code
Scaling structural learning with NO-BEARS to infer causal transcriptome networks
Constructing gene regulatory networks is a critical step in revealing disease mechanisms from transcriptomic data.
Enhancing high-content imaging for studying microtubule networks at large-scale
Such requirements are particularly challenging for high-throughput imaging, where researchers must make decisions related to the trade-off between imaging quality and speed.
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