Prediction of MoRFs in Protein Sequences with MLPs Based on Sequence Properties and Evolution Information
作者: Hao HeJiaxiang ZhaoGuiling Sun
作者单位: 1College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300350, China
刊名: Entropy, 2019, Vol.21 (7)
来源数据库: Multidisciplinary Digital Publishing Institute
DOI: 10.3390/e21070635
关键词: Molecular recognition featuresIntrinsically disordered proteinsMulti-layer perceptron
原始语种摘要: Molecular recognition features (MoRFs) are one important type of intrinsically disordered proteins functional regions that can undergo a disorder-to-order transition through binding to their interaction partners. Prediction of MoRFs is crucial, as the functions of MoRFs are associated with many diseases and can therefore become the potential drug targets. In this paper, a method of predicting MoRFs is developed based on the sequence properties and evolutionary information. To this end, we design two distinct multi-layer perceptron (MLP) neural networks and present a procedure to train them. We develop a preprocessing process which exploits different sizes of sliding windows to capture various properties related to MoRFs. We then use the Bayes rule together with the outputs of two trained...
全文获取路径: MDPI 

  • recognition 识别
  • preprocessing 预处理
  • features 特征
  • perceptron 感知器感知机
  • transition 转移
  • neural 神经系统的
  • disordered 混乱的
  • procedure 手续
  • trained 受过训练的
  • properties 道具