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In our work, we have done the cross-examination with mouse datasets and human datasets using a fully connected neural network (FCNN). This plays a vital role in protein sequencing and further examination of its helix structure. Secondly, our major agenda in our entire work was to focus on the result that we got when varying the length of the protein sequence while giving it as an input to our model. Recurrent Neural Networks can also be applied to prediction models as an alternative. Key Word: Protein structure classifier, mouse dataset, Human dataset, protein data bank (PDB)