2023/05/10 by Nam V. Nguyen, Nguyen, Phuong-Nam
Biochemistry, Genetics and Molecular Biology · Computer Science · #FOS: Biological sciences #FOS: Computer and information sciences #Metaheuristic Optimization Algorithms Research #Neural and Evolutionary Computing (cs.NE) #Other Quantitative Biology (q-bio.OT) #Protein Degradation and Inhibitors
paper · pdf · doi:10.48550/arxiv.2309.00001
openalex publication_date 2023/05/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The discovery of biomarker sets for a targeted pathway is a challenging problem in biomedical medicine, which is computationally prohibited on classical algorithms due to the massive search space. Here, I present a quantum algorithm named QuantAnts Machine to address the task. The proposed algorithm is a quantum analog of the classical Ant Colony Optimization (ACO). We create the mixture of multi-domain from genetic networks by representation theory, enabling the search of biomarkers from the multi-modality of the human genome. Although the proposed model can be generalized, we investigate the RAS-mutational activation in this work. To the end, QuantAnts Machine discovers rarely-known biomarkers in clinical-associated domain for RAS-activation pathway, including COL5A1, COL5A2, CCT5, MTSS1 and NCAPD2. Besides, the model also suggests several therapeutic-targets such as JUP, CD9, CD34 and CD74.