IBP-neuronal-gene-circuits-oncology

This perspective introduces the Intracellular Biological 
Perceptron (IBP), an original theoretical framework proposing 
neuronal-inspired synthetic gene circuits for weighted, 
multi-input intracellular cancer classification. Unlike 
existing Boolean AND-gate approaches, the IBP architecture 
mimics artificial neural network computation — integrating 
cancer-associated biomarkers (oncogenic microRNAs, 
transcription factor activities, metabolic flux indicators) 
as weighted inputs into a graded, probabilistic cancer 
classification output. A multi-layer extension — the 
Biological Deep Network (BDN) — is proposed for intracellular 
cancer staging. Applications in glioblastoma, pancreatic 
adenocarcinoma, and non-small cell lung cancer are discussed, 
alongside a four-phase experimental validation roadmap.