A Comparative Study on Filtering Protein Secondary Structure Prediction
Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine learning techniques and empirical rules and we found that combinations of the two lead to the highest improvement.
filtering protein secondary structure prediction machine learning structural bioinformatics bidirectional recurrent neural networks