Intersecções entre Computação Quântica e Bioinformática: Potenciais, Desafios e Aplicações Práticas

Abstract

As the volume of biological data continues to increase rapidly, es pecially in genomics and molecular biology, traditional computational approa ches have struggled to scale accordingly. This work presents a literature review focused on the intersection between quantum computing and bioinformatics, ex ploring the main concepts, methodologies, and applications that connect these two areas. The study maps how quantum algorithms and architectures are being considered to optimize classical bioinformatics tasks, and proposes a practical, incremental approach for integrating quantum computing into existing tools, such as the GATK, a toolkit widely used in bioinformatics for variant calling from sequencing data. Based on the analysis of recent scientific contributions and the evaluation of current challenges and opportunities, the study concludes that incorporating quantum subroutines into classical pipelines is conceptually viable, with the potential to accelerate specific stages, such as variant identifi cation and prioritization, without requiring a complete restructuring of existing workflows. Furthermore, it proposes a conceptual foundation to guide future research efforts interested in applying quantum computing to diverse problems in bioinformatics.