A novel model-based on FCM-LM algorithm for prediction of protein folding rate

作者：Liu, Longlong; Ma, Mingjiao^*; Cui, Jing

来源：Journal of Bioinformatics and Computational Biology, 2017, 15(4): 1750012.

DOI：10.1142/S0219720017500123

• Fuzzy cognitive map
• deep learning
• protein folding rate
• neural network
• FCM-LM algorithm

The prediction of protein folding rates is of paramount importance in describing the protein folding mechanism, which has broad applications in fields such as enzyme engineering and protein engineering. Therefore, predicting protein folding rates using the first-order of protein sequence, secondary structure and amino acid properties has become a very active research topic in recent years. This paper presents a new fuzzy cognitive map (FCM) model based on deep learning neural networks which uses data obtained from biological experiments to predict the protein folding rate. FCM extracts the important data features from the protein sequence which then initializes the deep neural networks effectively. It was found that the Levenberg-Marquardt (LM) algorithm for deep neural networks can improve the prediction accuracy of the protein folding rates. The correlation coeffcient between the predicted values and those real values obtained from experiments reached 0.94 and 0.9 in two independent numerical tests.

• 出版日期2017-8
• 单位中国海洋大学