I'm participating in a bioinformatics machine-learning seminar at my university. The main task is predicting binary classification of protein-protein interactions using sequence data as input.
One of the subtasks is familiarization with the dataset and presenting the dataset. Now I'm wondering which additional information I can get out of the sequence data.
I want to start out with binary classification for the protein interaction with the labels “Interact” and “Non-Interact. The dataset that I got provided consists of two fasta files. One containing the sequence header with the species and the corresponding amino-acid sequences ~300 entries. The other containing the exact same species header and the label “Interact” or "Non-interact”. Species are completely mixed.
Is there something interesting that I can additionally include in my analysis? I'm used to exploratory data analysis though this is different due to the nature of the protein sequences.