Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Abstract Imaging-based spatial transcriptomics provides single-cell resolution, but remains limited to targeted gene panels, leaving much of the transcriptome and cellular-state variation unobserved. Existing approaches infer unmeasured genes primarily through transcriptional alignment between spatial and reference datasets, which effectively recover broad cell identities, but may not fully capture context-dependent variation within cell types.
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
