DiaTrans
algorithm · Transformer (AR)
Transformer for DIA
| Kind | algorithm |
| Deep learning | yes |
| Acquisition | DIA |
| Also known as | Casanovo-DIA, Transformer-DIA |
| Family | Transformer (AR) |
Code
Live stars, open issues and last-push figures are on the Code activity chart.
Reported comparison
The comparison table this method’s own papers print, standardised: every value on a 0-1 scale, methods down the side, the measure and then the species across. These are numbers papers report about themselves and their baselines. They are not a leaderboard, and they do not compare across tables: each was produced by a different group, on the dataset named in its corner, with each baseline either retrained, run from released weights or quoted from another paper. Where the paper says which, it follows the method’s name (hover it for the sentence); most papers do not say. Bold is the best value in a column and underline the runner-up, our ranking rather than the paper’s own marks.
TABLE I
Transformer-Based De Novo Peptide Sequencing for Data-Independent Acquisition Mass Spectrometry, page 5: Precision comparison of Transformer-DIA, DeepNovo-DIA and PepNet.
| De novo sequencing of DIA data | Peptide precision | Amino acid precision | ||||
|---|---|---|---|---|---|---|
| UTI | OC | Plasma | UTI | OC | Plasma | |
| DiaTrans | 0.663 | 0.798 | 0.672 | 0.731 | 0.829 | 0.78 |
| DeepNovo-DIA | 0.403 | 0.417 | 0.383 | 0.566 | 0.547 | 0.702 |
| PepNet | 0.296 | 0.368 | 0.351 | 0.396 | 0.455 | 0.509 |
Papers describing it (2)
- Transformer-Based De Novo Peptide Sequencing for Data-Independent Acquisition Mass Spectrometry (2023, 2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE), peer-reviewed)
- Transformer-Based De Novo Peptide Sequencing for Data-Independent Acquisition Mass Spectrometry (2024, arXiv, postprint)
Paper using it
An application or evaluation that ran this method. It is not counted among its authors below.