Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules
Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules
复制标题
使用人工神经网络模拟 DNA 分子生化操作中的错误
DOI：
10.1109/tcbb.2021.3088525
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发表时间：
2021-06
期刊：
影响因子：
--
通讯作者：
Hao Qi
中科院分区：
文献类型：
--
作者：
Alan J. X. Guo;Hao Qi
— In recent years, the non-biological applications of DNA molecules have made considerable progress; most of these applications were performed in vitro , involving biochemical operations such as synthesis, amplification and sequencing. Because errors may occur with specific sequence patterns or experimental instruments, these biochemical operations are not completely reliable. Modeling errors in these biochemical procedures is an interesting research topic. For example, researchers have proposed several methods to avoid the known vulnerable sequence patterns in the study of storing binary information in DNA molecules. However, there are few end-to-end methods to evaluate these biochemical errors with regard to the DNA sequences. In this article, based on the data generated by a DNA storage research, we use artificial neural networks to predict whether a DNA sequence tends to cause errors in biochemical operations. Through comparative experiments and hyperparameter optimization, we analyze the known and potential problems in the research process. As a result, an end-to-end method to model the biochemical errors of DNA molecules in vitro through a computer system is proposed.
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影响因子：
5.5
作者：
Li H;Tian S;Li Y;Fang Q;Tan R;Pan Y;Huang C;Xu Y;Gao X
通讯作者：
Gao X
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DOI：
10.1093/bioinformatics/btp163
发表时间：
2009-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
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作者：
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通讯作者：
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发表时间：
2020
期刊：
Advances in Systems Analysis, Software Engineering, and High Performance Computing
影响因子：
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作者：
Menaga D.;R. S.
通讯作者：
Menaga D.;R. S.
DOI：
10.4018/978-1-5225-9096-5.ch007
发表时间：
2021-07
期刊：
Smart Computational Intelligence in Biomedical and Health Informatics
影响因子：
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作者：
A. Sinha;S. Gupta;Anurag Tiwari;Amrita Chaturvedi
通讯作者：
A. Sinha;S. Gupta;Anurag Tiwari;Amrita Chaturvedi
DOI：
10.4018/978-1-5225-7862-8.ch007
发表时间：
2019
期刊：
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影响因子：
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作者：
K. Lakhtaria;Darshankumar Modi
通讯作者：
K. Lakhtaria;Darshankumar Modi