The project involves creating a cross-scale, multi-dimensional reference space of the human proteome that covers healthy adult men and women from three major races worldwide. This reference space will provide a high-precision and comprehensive depiction of the human proteome, serving as fundamental data for proteomics-based navigation systems and systematic exploration of human body structure principles.

The project includes developing a state space of the human proteome across an entire life cycle - from reproduction, development, childbirth, growth, sexual maturity to aging. It also incorporates matrix-style dynamic data flow groups on how four major dietary patterns and five major survival environments interact with this life cycle. Through this approach we can understand evolutionary processes and laws of humans in different spatial-temporal dimensions; recognize digital expression modes and developmental rules of diseases during abnormal processes; determine directions and transformational rules for sub-health status or pathological states based on physiological conditions.

A navigation system based on both reference-state spaces will be established using cutting-edge technologies such as artificial intelligence (AI), big data analysis techniques (BDAT), multi-scale modeling etc., which will enable accurate monitoring of health status changes through warning models for abnormal states while providing precise "navigation" from an abnormal state back to normalcy.