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.

aligning DNA and protein sequences using dynamic programming

A compilation of all the programs in my bioinformatics course

Implementing the Smith-Waterman algorithm in Python

Implement parallel Smith Waterman algorithm on CUDA

Bio informatics course materials for NEUB students.

🧬 Distributing Local Sequence Alignment using Volunteer Computing

Next.js project implementing bioinformatics algorithms, including Needleman-Wunsch and Smith-Waterman, for sequence alignment with a modern web interface. ICSI310 ,Introduction to Bioinformatics

The repository contain directories of projects done during the bioinformatics degree program

AlnSeq runs a c coded Smith Waterman, Needleman Wunsch, and an Hirschberg.

A C++ project to detect mutations on DNA sequence, comparing two DNA samples. This project was built based on a Supercomputing subject and some classic algorithms are used in this project, such as Smith Waterman, Random Local Search and Exaustive Search

NodeJs implementation of Smith-Waterman- and Needleman-Wunsch-Algorithm for Arrays of Objects

The Smith-Waterman algorithm finds the optimal alignment of two sequences using dynamic programming techniques; Smith-Waterman is commonly used for DNA sequence alignment

Implementations of Needleman-Wunsch (global alignment) and Smith-Waterman (local alignment) algorithms using Python.

A parallel implementation of Smith-Waterman algorithm for determining similar regions between two strings of nucleic acid sequences or protein sequences.

MSc Biology C++ Course Assignment. A program that can either perform a global, or local sequence alignment. Implementation of the Smith-Waterman and Needleman-Wunsch algorithms.

R package for global alignment between two genomic sequences

This repository collects materials, notebooks, and examples related to computational methods applied to biological data. It is organized in folders by topic or instructor and includes scripts, input files, and exam preparation exercises. Useful for study, practice, and reviewing core concepts in computational biology and data analysis.

A Go implementation of the Smith–Waterman algorithm