A comparison study on protein fold recognition

Although two proteins may be structurally similar, they may not have significant sequence similarity. The recognition of protein fold structures without relying on sequence similarity is a complex task. This work presents a comparison study on the recognition of 3-dimensional protein folds by Machine Learning models. Combinations of neural networks were trained by bagging and arcing with two datasets available online (http://www.nersc.gov/). Our results improved the average predictive accuracy obtained by Support Vector Machines in previously published work.