| dc.contributor | 資科系 | - |
| dc.creator (作者) | 張家銘 | - |
| dc.creator (作者) | Chang, Jia-Ming | - |
| dc.creator (作者) | Lin, Yang Ming | - |
| dc.creator (作者) | Chen, Ching-Tai | - |
| dc.date (日期) | 2019-12 | - |
| dc.date.accessioned | 2-Sep-2020 09:11:18 (UTC+8) | - |
| dc.date.available | 2-Sep-2020 09:11:18 (UTC+8) | - |
| dc.date.issued (上傳時間) | 2-Sep-2020 09:11:18 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/131396 | - |
| dc.description.abstract (摘要) | Tandem mass spectrometry allows biologists to identify and quantify protein samples in the form of digested peptide sequences. When performing peptide identification, spectral library search is more sensitive than traditional database search but is limited to peptides that have been previously identified. An accurate tandem mass spectrum prediction tool is thus crucial in expanding the peptide space and increasing the coverage of spectral library search. | - |
| dc.format.extent | 3288343 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | BMC Genomics, Vol.20, Supplement 9, 906 | - |
| dc.subject (關鍵詞) | Peptide ; Mass spectrum ; Tandem mass spectrometry ; Spectral library search ; Protein identification ; Machine learning ; Deep learning ; Deep convolutional neural networks | - |
| dc.title (題名) | MS2CNN: Predicting MS/MS spectrum based on protein sequence using deep convolutional neural networks | - |
| dc.type (資料類型) | article | - |
