Classification of deep-sea cold seep bacteria by transformer combined with Raman spectroscopy | |
Liu, Bo2,3; Liu, Kunxiang2,3; Qi, Xiaoqing1; Zhang, Weijia1; Li, Bei2,3 | |
刊名 | SCIENTIFIC REPORTS |
2023-02-24 | |
卷号 | 13期号:1 |
文献子类 | 期刊论文 |
英文摘要 | Raman spectroscopy is a rapid analysis method of biological samples without labeling and destruction. At present, the commonly used Raman spectrum classification models include CNN, RNN, etc. The transformer has not been used for Raman spectrum identification. This paper introduces a new method of transformer combined with Raman spectroscopy to identify deep-sea cold seep microorganisms at the single-cell level. We collected the Raman spectra of eight cold seep bacteria, each of which has at least 500 spectra for the training of transformer model. We compare the transformer classification model with other deep learning classification models. The experimental results show that this method can improve the accuracy of microbial classification. Our average isolation level accuracy is more than 97%. |
WOS研究方向 | Science & Technology - Other Topics |
语种 | 英语 |
WOS记录号 | WOS:000942280900030 |
内容类型 | 期刊论文 |
版本 | 出版稿 |
源URL | [http://ir.idsse.ac.cn/handle/183446/10155] |
专题 | 深海科学研究部_深海生物学研究室_深海微生物细胞生物学研究组 |
作者单位 | 1.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Hainan, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 3.Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, State Key Lab Appl Opt, Changchun 130033, Peoples R China; |
推荐引用方式 GB/T 7714 | Liu, Bo,Liu, Kunxiang,Qi, Xiaoqing,et al. Classification of deep-sea cold seep bacteria by transformer combined with Raman spectroscopy[J]. SCIENTIFIC REPORTS,2023,13(1). |
APA | Liu, Bo,Liu, Kunxiang,Qi, Xiaoqing,Zhang, Weijia,&Li, Bei.(2023).Classification of deep-sea cold seep bacteria by transformer combined with Raman spectroscopy.SCIENTIFIC REPORTS,13(1). |
MLA | Liu, Bo,et al."Classification of deep-sea cold seep bacteria by transformer combined with Raman spectroscopy".SCIENTIFIC REPORTS 13.1(2023). |
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