Optimizing Sequence Alignment Performance and Accuracy in the scikit-bio Library: Algorithmic Enhancements and Benchmarking

This project presents a high-performance implementation of Gotoh’s pairwise sequence alignment algorithm within the scikit-bio Python library, optimized using Cython for computational efficiency. Designed to address the limitations of scikit-bio’s original pure Python alignment function, the new implementation achieves substantial performance gains—exceeding a 2800x speedup on longer sequences—while maintaining accuracy and full compatibility with the existing scikit-bio API. Emphasis was placed on modular code structure, enabling ease of use, maintainability, and seamless substitution between global and local alignment modes. Benchmarking against BioPython, BioTite, and the prior scikit-bio implementation confirms the new algorithm’s competitive runtime and practical value for real-world bioinformatics workflows. This work demonstrates the potential for integrating low-level performance enhancements within high-level, user-friendly scientific computing environments.