SEMO 算法
SEMO Algorithm
The transformation engine from life-state characterization to intervention plans
Full Definition
SEMO is a pre-trained network medicine model that partitions the global human protein-protein interaction (PPI) network into smaller subnetworks and statistically compares the target gene sets of chemical compounds against non-target gene sets to quantify their potential effects. It bridges the gap from state characterization to intervention plan generation, filling the systematic void between 'knowing the state' and 'generating a plan' in medicine.
Deduction from First Principles
Deduced from the first principle:
1. If life is a capability ensemble, then the goal of intervention is to restore or enhance specific capabilities.
2. The molecular basis of capabilities can be modeled through network pharmacology approaches.
3. Therefore, an algorithm can be constructed to automatically derive intervention plans from capability state characterizations.
Why It Matters
Existing medical AI primarily focuses on prediction and diagnostic assistance, lacking systematic generative capacity from state to intervention. SEMO fills this gap and serves as the core engine for translating capomics into practical applications.
Related Essays
Related Papers
- 从网络药理学到能力组学，《中国药理学与毒理学杂志》2023年S1期