Prediction of amyloid aggregation rates by machine learning and feature selection

A novel data-based machine learning algorithm for predicting amyloid aggregation rates is reported in this paper. Based on a highly nonlinear projection from 16 intrinsic features of a protein and 4 extrinsic features of the environment to the protein aggregation rate, a feedforward fully connected...

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Veröffentlicht in:	The Journal of chemical physics 2019-08, Vol.151 (8), p.084106-084106
Hauptverfasser:	Yang, Wuyue, Tan, Pengzhen, Fu, Xianjun, Hong, Liu
Format:	Artikel
Sprache:	eng
Schlagworte:	Agglomeration Algorithms Artificial intelligence Correlation analysis Forecasting Helices Machine learning Neural networks Physics Predictions Principal components analysis Proteins Regression analysis Support vector machines
Online-Zugang:	Volltext
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