2, ATTCry model for protein crystallization prediction consists of six modules: input layer, embedding layer, multi-scale convolutional neural network (CNN) layers, multi-head self-attention layers, fully-connected hidden layers, and output layer.
Nov 6, 2021
ATTCry: Attention-based neural network model for protein crystallization prediction. Code for our paper "ATTCry: Attention-based neural network model for ...
Several CNN or attentionbased architectures have been implemented for the prediction of protein crystallization propensity and for crystallization monitoring ( ...
ATTCry: Attention-based neural network model for protein ...
www.semanticscholar.org › paper › ATT...
A novel deep learning framework, named SADeepcry, is proposed, which can be used to estimate the three steps (protein material production, purification and ...
Nov 6, 2021 · ATTCry: : Attention-based neural network model for protein crystallization prediction. Authors: Chen Jin. Chen Jin. College of Computer Science ...
Article on ATTCry: Attention-based neural network model for protein crystallization prediction, published in Neurocomputing 463 on 2021-08-16 by Chen Jin+3.
ATTCry: Attention-based neural network model for protein crystallization prediction ... prediction using self-attention and auto-encoder networks. Shaokai ...
ATTCry is an attention-based neural network for crystallization propensity prediction. ATTCry can extract both local and global features of protein sequences.
ATTCry: Attention-based neural network model for protein crystallization prediction. Neurocomputing. 2021;463:265–274. doi: 10.1016/j.neucom.2021.08.029 ...
Oct 22, 2024 · CLPred has been steadily improved over the previous window-based neural networks, which is able to predict crystallization propensity with high ...