Bioinformatics Algorithms implemented in Rust for bioinformatics learners, with a book.
This repository is for those who want to seriously learn bioinformatics algorithms without learning C/C++
- Bioinformatics algorithms, from those "ancient" ones found only in textbooks to the state-of-the-art ones currently being used and discussed
- You'll understand those algorithms, and be able to implement them by yourself.
- This is a very young project initiated on 2020-09-12 and maintained by an undergraduate student, so currently don't expect too much.
- Simple programming languages such as Python, Ruby and Perl are popular among biologists. That's why BioPython, BioRuby and BioPerl are much popular than SeqAn (C++).
- Python, Ruby and Perl are too slow for core algorithms in bioinformatics, and these algorithms are traditionally implemented in C/C++.
- C/C++ is difficult for many biologists. Of those interested in the internals of the bioinformatics tools they use, few take a step further to learn C/C++.
- A young language called Rust turns out to be both simple and fast (as fast as C). Indeed, some algorithms implemented in rust-bio outperforms their counterparts in SeqAn.
- Thus I believe Rust is the perfect language for bioinformatics. People who want to learn bioinformatics algorithms seriously should learn Rust.
- This repository helps you to learn bioinformatics with Rust.
- It is not just a bunch of code to be downloaded and run. It helps you to learn by guiding you through the steps to reach the final solution. Any special implementation details are thoroughly explained, and the only prerequisite is Chapters 1-14 of The Book.
Read the book here.
Contributions of any form are welcome!
Currently this project is at is very early stage of development, so I don't mind any breaking changes.
In addition, English is not my first language, so I would be grateful if you can help rephrasing words that can be improved!
✅: Algorithm Implemented ✅✅: Comments Added ✅✅✅: Documentation Finished
| Implemented | Author | Space complexity | Global | Local | Semiglobal | Affine Gap | Log Gap |
|---|---|---|---|---|---|---|---|
| ✅ | Needleman-Wunsch | O(nm) | ✅ | ||||
| ✅ | Smith-Waterman | O(nm) | ✅ | ||||
| Gotoh | O(nm) | ✅ | ✅ | ||||
| Hirshberg | O(n) | ✅ | |||||
| Myers-Miller (1988) | O(n) | ✅ | ✅ | ||||
| Huang (1991) | O(n) | ✅ | ✅ |
MUSCLE
ClustalW