Presently, I am coding a neural network for protein secondary structure prediction. Initially, I thought of predicting contact maps. But, the I coudn’t find contact map data for proteins. Moreover, parsing the PDB files and then creating a contact map seemed as a daunting task to me.
Therefore, I chose the secondary structure prediction. Well, what I am gonna do is to input a amino acid sequence and then predict secondary structure for each residue. Current methods achieve around 75-80% accuracy, so I will try to achieve atleast 75% accuracy.
My process will be a 3 stage process. First two will involve a neural network and the third one assigns confidence to prediction based on statistical information.
Any ideas, comments or suggestions?