A Computational Framework for Genomics

A Computational Framework for Genomics ABSTRACT. Genomic data comparison and storage play a critical role in forensic geneticsand large-scale genomic investigations, yet traditional approaches often require days toprocess and compare complex genetic datasets. This paper presents an open-source,CPU-based computational framework that reduces genomic comparison times from daysto seconds while maintaining forensic-grade accuracy. The proposed system builds upon akernel-based genomic representation combined with optimized data structures and parallelprocessing strategies, enabling high-throughput analysis on classical hardware.Unlike GPU-dependent solutions, the framework is designed to operate eciently onstandard personal computers, signicantly lowering hardware requirements and deploy-ment costs. By adopting a fully local execution model, the proposed approach enhancesdata privacy, security, and reproducibility, which are essential in forensic and institutionalgenomic workows. The open-source implementation further promotes transparency andmethodological interpretability, facilitating adoption by domain experts. Performanceevaluations conducted on benchmark forensic DNA datasets demonstrate substantial im-provements in processing speed while preserving the accuracy and reliability requiredfor forensic applications. Overall, this work establishes a scalable and accessible com-putational foundation for rapid genomic comparison, with potential applicability beyondforensic genetics to other large-scale genomic analysis domains.