https://www.selleckchem.com/TGF-beta.html
Prediction of protein solubility is an indispensable prerequisite for pharmaceutical research and production. The general and specific objective of this work is to design a new model for predicting protein solubility by using protein sequence feature fusion and deep dual-channel convolutional neural networks (DDcCNN) to improve the performance of existing prediction models. The redundancy of raw protein is reduced by CD-HIT. The four subsequences are built from protein sequence one global and three locals. The global subsequence is the entire p
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