Kaiko
downstream-application · CNN + RNN
Kaiko: downstream-application · CNN + RNN. Deep-learning (CNN + RNN) de novo peptide sequencer trained on 5 M peptide-spectrum matches from 55 phylogenetically diverse bacteria. Identifies microbial community…
Deep-learning (CNN + RNN) de novo peptide sequencer trained on 5 M peptide-spectrum matches from 55 phylogenetically diverse bacteria. Identifies microbial community members directly from metaproteomic MS/MS, then builds sample-specific protein databases without requiring matched metagenomes: validated on native soil microbiome samples.
| Kind | downstream-application |
| Deep learning | yes |
| Acquisition | DDA |
| Family | CNN + RNN |
| Application area | Metaproteomics |
Code
Live stars, open issues and last-push figures are on the Code activity chart.
Data
What the papers describing this method trained it on and reported its results on, as each paper states it. A version is named only where the paper names one.
Deposited
- DeNovo Peptide Identification Deep Learning Test Set (as deposited) · 2018 preprint, 2022 peer-reviewed
- DeNovo Peptide Identification Deep Learning Training Set (as deposited) · 2018 preprint, 2022 peer-reviewed
- Soil metaproteomics data analysis based on de novo sequencing with the deep learning-based Kaiko model (as deposited) · 2022 peer-reviewed
Also used, purpose not recorded
- DeNovo Peptide Identification Deep Learning Test Set (as deposited) · 2020 preprint
- DeNovo Peptide Identification Deep Learning Training Set (as deposited) · 2020 preprint
- Simplified Human Intestinal Microbiota (SIHUMIx) LC-MS/MS dataset (as deposited) · 2022 peer-reviewed
- Soil metaproteomics data analysis based on de novo sequencing with the deep learning-based Kaiko model (as deposited) · 2020 preprint
Papers describing it (3)
- Proteomics of natural bacterial isolates powered by deep learning-based de novo identification (2018, bioRxiv, preprint)
- Uncovering hidden members and functions of the soil microbiome using de novo metaproteomics (2020, bioRxiv, preprint)
- Uncovering Hidden Members and Functions of the Soil Microbiome Using De Novo Metaproteomics (2022, Journal of Proteome Research, peer-reviewed)