Abstract
Background
Genetic algorithms(GAs) are a class of optimization algorithms inspired by the process of natural selection and genetics. In genomics, GAs face limitations such as extensive computational time, and population size requirement, hindering practical applications. In response, the BioGA package offers users the ability to rapidly analyze and optimize high throughput genomic data using genetic algorithms. With core functions implemented in C++ to enhance speed and efficiency, BioGA provides a user-friendly interface for integration within R.
This package utilizes the principles of genetic algorithms, which mimic the process of natural selection to find optimal solutions, making it a powerful tool for handling large-scale genomic data analysis and optimization tasks. This integration of genetic algorithms within the BioGA framework provides a robust and versatile tool, offering an effective methodology for addressing complex optimization challenges in genomics and related fields.