protein-secondary-structure-predictor

Created for my Introduction to Bioinformatics class.

Uses sklearn's MLPClassifier and a protein's amino acid sequence to predict its secondary structure.

List of Files

• .gitignore: a gitignore
• dataset.txt: the 22 sequences and their structures used to train the neural network
• predictor.ipynb: a jupyter notebook that runs the program
• predictor.py: all the python code from the jupyter notebook

Steps to run

1. Clone the repository
2. Open and run the predictor.ipynb file using Jupyter Notebook
3. Create a .txt file with the sequences, follow sample_predict_seq.txt for formatting
4. Go to this line in the code: file_predict=open("sample_predict_seq.txt", "r") and replace "sample_predict_seq.txt"
   with the path to your .txt file with the sequences you want to predict
5. Run the notebook