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…

Needleman-Wunsch and Smith-Waterman algorithms in python

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

Collection of sequence alignment algorithms.

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

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.

Fuzzy finder algorithms a la Smith-Waterman for Zig.

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

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

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

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…

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 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.…

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

GPU-based DNA sequence alignment program using Smith-Waterman

Examples for SDAccel 2017.1+ on AWS F1 instances