We have extended the standard Needleman-Wunsch Algorithm to account for affine gap penalties. In this repository, we have provided:
- Implementation of the standard Needleman-Wunsch algorithm. at nwAffineGapPenalties.py:
- Implementation of Needleman-Wunsch with affine gap penalties at nwag2.py:
- You need to import the .py files. You may set a few parameters for each particular algorithm as such delta, gap open penalty, gap extension penalty, and so on. Otherwise, it would run with default values.
We have provided benchmarking notebook Benchmarking_on_Balibase_dataset.ipynb.
- Import the desired algorithm
- Run the notebook to benchmark the algorithm on the BAliBASE dataset. Required datasets and Python packages will be automatically downloaded when the notebook is executed.