There are 2 repositories under smith-waterman topic.
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
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.
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
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
Javascript implementation of the Smith-Waterman algorithm for sequence alignment.
A collection of string comparisons algorithms
Examples for SDAccel 2017.1+ on AWS F1 instances
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.
DNA Sequence Alignment with Dynamic Programming Implementation using the Needleman-Wunsch Algorithm and Smith-Waterman Algorithm.
Comparison of Protein Sequence Embeddings to Classify Molecular Functions
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.
A simple parallel implementation of Smith Waterman sequence alignment algorithm.
Pairwise Sequence Aligment Tool (PSAT) a simple application to align sequences.
Global and Local Sequence Alignment
Parallel and Distributd Computing Project
Tool for exploring sequence alignment algorithms
Solidity implementations of well-known pairwise alignment methods such as Needleman-Wunsch's global sequence alignment and the Smith-Waterman local sequence alignment algorithm.
Biosequence analysis library
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
🔬🧬 Algoritmo de alinhamento Smith Waterman em Python
Bilkent University CS 481 Bioinformatics Algorithms assignments