A deep proteome and transcriptome abundance atlas of 29 healthy human tissues
benchmark · DDA · 1 version · 6 papers
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues
| Kind | benchmark |
| Acquisition | DDA |
| Organisms | Homo sapiens (human) |
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues
Versions
as deposited
released 2019-07-10
Where it lives:
- PRIDE · PXD010154
Trained on by (2)
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2024) peer-reviewed as deposited
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2023) preprint as deposited
Evaluated on by (2)
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2024) peer-reviewed as deposited
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2023) preprint as deposited
Used by (4)
Papers that ran on it where the catalog has not recorded whether for training or for evaluation.
- Mass Spectrometry-Based Profiling of Personalized Immunopeptidomes in Thai Renal Cell Carcinoma (2026) peer-reviewed as deposited
- Learning from tandem mass spectra at scale with a self-supervised foundation model for proteomics (2026) preprint as deposited
- NovoBoard: A Comprehensive Framework for Evaluating the False Discovery Rate and Accuracy of De Novo Peptide Sequencing (2024) peer-reviewed as deposited
- NovoBoard: a comprehensive framework for evaluating the false discovery rate and accuracy of de novo peptide sequencing (2024) preprint as deposited
Methods on these papers (4)
- InstaNovo-FM algorithm
- NovoBoard benchmark
- Spectralis post-processor
- Thai RCC personalised immunopeptidomics downstream-application
Taken from the describing links only, so a paper that merely ran a tool on this data does not make that tool a method of it.