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.org/abs/1910.09020.

Needleman-Wunsch and Smith-Waterman algorithms in python

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

(Moved to Codeberg) Fuzzy finder algorithms a la Smith-Waterman for Zig.

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.

Collection of sequence alignment algorithms.

Collection of string similarity and distance algorithms in PHP including Levenshtein, Damerau-Levenshtein, Jaro-Winkler, and more

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

Python implementation of several sequence alignment algorithms such as Waterman-Smith-Beyer, Gotoh, and Needleman-Wunsch intended to calculate distance, show alignment, and display the underlying matrices.

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

A collection of string comparisons algorithms

Tool for exploring sequence alignment algorithms

Implementation of Needleman-Wunsch, Smith-Waterman, Hirschberg and affine bioinformatics algorithms for alighning biological sequences

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

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

The first work to provide a comprehensive survey of a prominent set of algorithmic improvement and hardware acceleration efforts for the entire genome analysis pipeline used for the three most prominent sequencing data, short reads (Illumina), ultra-long reads (ONT), and accurate long reads (HiFi). Described in arXiv (2022) by Alser et al. https://arxiv.org/abs/2205.07957

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

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.org/abs/2003.00110.

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

A C++ implementation of the Smith - Waterman algorithm. The system consists of 3 different implementations: the one is sequential, while the other two parallelize the execution in a coarse and a fine level respectively, with the use of multithreading.

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

Examples for SDAccel 2017.1+ on AWS F1 instances

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🚀 R interface for SSW, a fast implementation of the Smith-Waterman algorithm using SIMD

GPU-based DNA sequence alignment program using Smith-Waterman

Dynamic Programming in Erlang.

Comparison of Protein Sequence Embeddings to Classify Molecular Functions

A simple parallel implementation of Smith Waterman sequence alignment algorithm.

Fast Smith-Waterman algorithm for Ruby