Go metrics for calculating string similarity and other string utility functions

SneakySnake:snake: is the first and the only pre-alignment filtering algorithm that works efficiently and fast on modern CPU, FPGA, and GPU architectures. It greatly (by more than two orders of magnitude) expedites sequence alignment calculation for both short and long reads. Described in the Bioinformatics (2020) by Alser et al. https://arxiv.o…

SIMD C/C++ library for massive optimal sequence alignment (local/SW, infix, overlap, global)

Needleman-Wunsch and Smith-Waterman algorithms in python

This work implements a dynamic programming algorithm for performing local sequence alignment. Through parallelism, it can run 136X times faster than a software running the same algorithm.

A collection of string comparisons algorithms

A simple application to calculate similarity between two files (text document) using Smith-Waterman algorithm that is used originally to determine similar region between two sequences of DNA

A systematic survey of algorithmic foundations and methodologies across 107 alignment methods (1988-2021), for both short and long reads. We provide a rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read alignment. Described by Alser et al. at https://arxiv.…

A Python module to calculate alignment between two sequences using EMBOSS' needle, stretcher, and water

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

C/C++ implementation of the Smith-Waterman algorithm by using SIMD operations (e.g SSE4.1)

A simple parallel implementation of Smith Waterman sequence alignment algorithm.

DNA Sequence Alignment with Dynamic Programming Implementation using the Needleman-Wunsch Algorithm and Smith-Waterman Algorithm.

Parallel and Distributd Computing Project

Solidity implementations of well-known pairwise alignment methods such as Needleman-Wunsch's global sequence alignment and the Smith-Waterman local sequence alignment algorithm.

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).

Implementing the Smith-Waterman algorithm in Python

Javascript implementation of the Smith-Waterman algorithm for sequence alignment.

Smith Waterman in C