A Foundational Model for Biological Logic and Disease
Year: 2025
Type: preprint
Abstract: Biology and medicine mistake complexity for understanding. We build black-box AI models and stockpile terabytes of omics data, yet the logic of life remains hidden in plain sight. The cell, nature’s smallest decision-maker computes not by probability, but by logic: “on” or “off,” “commit” or “retract.” Boolean mathematics decodes this digital decision-making, transforming analog molecular noise into invariant “if–then” rules that persist across tissues, species, and diseases. Simultaneously, by quantifying how populations shift between binary states, Boolean frameworks map disease as an analog continuum—dynamic, graded, reversible and objectively measurable. By deciphering both the binary decisions and the graded population shifts that shape disease, this approach replaces static biomarkers with mechanistic rules—and advances a new premise: if life computes in logic, medicine should too.
Authors: Sinha, Saptarshi, Ghosh, Pradipta
Institution: University of California San Diego
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7101434189