Needleman-Wunsch and Smith-Waterman algorithms in python

Cython bindings and Python interface to Opal, a SIMD-accelerated database search aligner.

Comparison of Protein Sequence Embeddings to Classify Molecular Functions

Less-wrong single-file Numba-accelerated Python implementation of Gotoh affine gap penalty extensions for the Needleman–Wunsch, Smith-Waterman, and Levenshtein algorithms for sequence alignment

Global and Local Sequence Alignment

Implementing the Smith-Waterman algorithm in Python

This project includes Needleman-Wunsch and Smith-Waterman algorithms and their afine gap variations (Gotoh) written to work with Cython, PyPy and Numba. Numba JIT shows greater performance. For Best performance use gotoh_jit.py to get only the best score and use gotoh_jit_traceback to get the best alignment

Biosequence analysis library

🔬🧬 Algoritmo de alinhamento Smith Waterman em Python

El presente trabajo muestra la aplicación de algoritmos de alineación de secuencias conocidos como needleman-wunsch (global), smith-waterman (local) y semi-global con sus variantes (kband o afín de costo por gap).

Lots of protein

Parallelizing the Smith-Waterman alignment algorithm using mpi4py

Implementation of K-means that categorizes sequences into groups based on similarity score derived from Smith-Waterman algorithm.

Expanded version of the traditional Smith Waterman algorithm for local alignment

Text Similarity Analysis, POS tagging, Hidden markov models, Dependency parser

Algorithms to solve bioinformatics problems

Easy to use and modify implementation of Smith-Waterman Algorithm.

Python Implementation of the Smith-Waterman Algorithm for Bioinformatics

💻 Project for the course of Algorithms for Bioinformtics