Paper Title
Pro Gen-Q Quantum-Driven AI for Multi-Omics Mutation Profiling And Therapeutic Stratification

Abstract
ProGen-Q is a bioinformatics platform designed to study the relationship between genetic variations, protein structure, and therapeutic response. It integrates genomic variant interpretation, protein folding prediction, and treatment prioritization within a unified framework. The system analyzes mutations, including single nucleotide changes, to determine their effect on amino acid sequences and protein stability. These structural alterations are studied in the context of disease-related information to interpret their biological significance. The platform combines genomic, proteomic, and transcriptomic data to support comprehensive analysis. A computational model incorporating quantum-inspired optimization is used to enhance parameter tuning and solution exploration, enabling improved identification of patterns associated with disease conditions and treatment outcomes. Based on observed structural changes, the system compares protein features with known therapeutic compounds and suggests suitable treatment options. ProGen-Q supports both preloaded datasets and real-time clinical data, providing a structured approach for informed clinical decision-making. Keywords - Bioinformatics, Genomic Variants, Multi-omics Integration, Protein Structure Prediction, Quantum-Inspired Optimization, Therapeutic Prioritization, Precision Medicine.