Variable Site-Occupancy Classification of N-Linked Glycosylation Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Variable Site-Occupancy Classification of N-Linked Glycosylation Using Artificial Neural Networks

Published:2005-12-02 Issue:6 Volume:21 Page:1653-1662
ISSN:8756-7938
Container-title:Biotechnology Progress
language:en
Short-container-title:Biotechnol. Prog.

Author:

Senger R.S.,Karim M.N.

Publisher

Wiley

Subject

Biotechnology

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Two SERPINC1 variants affecting N-glycosylation of Asn224 cause severe thrombophilia not detected by functional assays;Blood;2022-07-14

2. Advanced strategies in glycosylation prediction and control during biopharmaceutical development: Avenues toward industry 4.0;Biotechnology Progress;2022-07-12

3. Process intensification to produce a difficult‐to‐express therapeutic enzyme by high cell density perfusion or enhanced fed‐batch;Biotechnology and Bioengineering;2021-05-13

4. Incorporating a transfer learning technique with amino acid embeddings to efficiently predict N-linked glycosylation sites in ion channels;Computers in Biology and Medicine;2021-03

5. Harnessing the potential of artificial neural networks for predicting protein glycosylation;Metabolic Engineering Communications;2020-06

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