Decoding Spatial Programs in Human Glioblastoma Through Surprisal Information-Theoretical Analysis

Abstract excerpt

Glioblastoma (GBM) is a highly heterogeneous and invasive brain tumor in which complex interactions among tumor cells, immune cells, and neurons shape disease progression and therapeutic resistance. Resolving spatial patterns programs in glioblastoma (GBM) requires analytical approaches that go beyond variance-driven embeddings. Here, we applied thermodynamic surprisal analysis, an information-theoretic decomposit...

Topics

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• Brain Neoplasms
• Case-Control Studies
• Glioblastoma
• MicroRNAs
• Phenotype
• Stochastic Processes
• Thermodynamics

Identifiers and source

Literature Corpus work

41c8c8e1-780c-5f12-a748-607e4fa2fe15

DOI

10.64898/2026.06.23.733938