AI RESEARCH
On the Recoverability of Causal Relations from Bulk Gene Expression Data
arXiv CS.LG
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ArXi:2606.00568v1 Announce Type: new Bulk gene expression profiling, which aggregates pooled RNA across cells within a biological sample, remains important in the single-cell era because it is typically less noisy, sensitive, and cost-effective than single-cell assays. Accordingly, a growing body of computational methods seeks to recover causal relations among genes from bulk expression data.