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MetabolomicsLipidCreator workbench to probe the lipidomic landscape - Collision Energy Optimization and Fragment Intensity Prediction for Lipid Mediators, Thermo QExactive HF

Here we present LipidCreator, a software that fully supports targeted lipidomics assay development. LipidCreator offers a comprehensive framework to compute MS/MS fragment masses for over 60 lipid classes. LipidCreator provides all functionalities needed to define fragments, manage stable isotope...

2020-04-15 | MTBLS1333 | MetaboLights
MetabolomicsLipidCreator workbench to probe the lipidomic landscape - Collision Energy Optimization and Fragment Intensity Prediction for Lipid Mediators, Agilent QTof

Here we present LipidCreator, a software that fully supports targeted lipidomics assay development. LipidCreator offers a comprehensive framework to compute MS/MS fragment masses for over 60 lipid classes. LipidCreator provides all functionalities needed to define fragments, manage stable isotope...

2020-04-15 | MTBLS1334 | MetaboLights
ProteomicsSpectral Cruncher: A Visualization Tool Integrating Manual Curation, Ion-Intensity Prediction, and De Novo Tag Generation
Here's a suggested Project Description for your PRIDE submission: Project Description This dataset contains mass spectrometry raw files used as training data for SpecFormer, a transformer-based ion intensity prediction model integrated within PatternLab for Proteomics (Spectral Cruncher module). Th...
ORGANISM(S): Mus musculus (Mouse) Homo sapiens (Human) 
2026-02-16 | PXD069898 | Pride
Ion intensity prediction Multi-species omics Single-cell proteomics 
ProteomicsFragment ion intensity prediction improves the identification rate of non-tryptic peptides in TimsTOF
Immunopeptidomics plays a crucial role in identifying targets for immunotherapy and vaccine development. Because the generation of immunopeptides from their parent proteins does not adhere to clear-cut rules, rather than being able to use known digestion patterns, every possible protein subsequence ...
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) 
2023-07-17 | MSV000092456 | MassIVE
ProteomicsProsit: Proteome-wide prediction of peptide tandem mass spectra by deep learning
In this study, we extended the ProteomeTools peptide library (PROPEL, see PXD004732 and PXD010595) to train a deep neural network resulting in chromatographic retention time and fragment ion intensity predictions for (tryptic) peptides that exceed the quality of the experimental data.
ORGANISM(S): Drosophila Melanogaster (ncbitaxon:7227) Escherichia Coli (ncbitaxon:562) Saccharomyces Cerevisiae (ncbitaxon:4932) Homo Sapiens (ncbitaxon:9606) Caenorhabditis Elegans (ncbitaxon:6239) 
2021-03-12 | MSV000087047 | MassIVE
UnknownFragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF.
Not available
S-EPMC11087512 | biostudies-literature
ProteomicsHigh quality MS/MS spectrum prediction for data-dependent and -independent acquisition data analysis
Peptide fragmentation spectra are routinely predicted in the interpretation of mass spectrometry-based proteomics data. Unfortunately, the generation of fragment ions is not well enough understood to estimate fragment ion intensities accurately. Here, we demonstrate that machine learning can predict...
ORGANISM(S): Homo sapiens (Human) 
2019-03-13 | PXD010382 | Pride
Deep learning Dia Machine learning Intensity prediction Andromeda 
ProteomicsProteomeTools â?? Part II - Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning
"The ProteomeTools project aims to derive molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we describe the second iteration of the generation and multimodal LC-MS/MS analysis of >220,000 synthetic tryptic peptides representing nearly all c...
ORGANISM(S): Homo Sapiens (ncbitaxon:9606) 
2020-07-21 | MSV000085805 | MassIVE
ProteomicsSpectral prediction features as a solution for the search space size problem in proteogenomics
Proteogenomics approaches often struggle with the distinction between right and false peptide-to-spectrum matches as the database size enlarges. However, features extracted from tandem mass spectrometry intensity predictors can enhance the peptide identification rate and can provide extra confidence...
ORGANISM(S): Homo sapiens (Human) 
2021-03-26 | PXD022280 | Pride
Proteogenomics  spectrum predictor  nanopore sequencing  ribosome profiling  rna-seq  ms2pip  prosit  intensity features  machine learning  hct116  percolator  maxquant 
ProteomicsProsit: Proteome-wide prediction of peptide tandem mass spectra by deep learning
In this study, we extended the ProteomeTools peptide library (PROPEL, see PXD004732 and PXD010595) to train a deep neural network resulting in chromatographic retention time and fragment ion intensity predictions for (tryptic) peptides that exceed the quality of the experimental data.
ORGANISM(S): Homo sapiens (Human) Escherichia coli Drosophila melanogaster (Fruit fly) Saccharomyces cerevisiae (Baker's yeast) Caenorhabditis elegans 
2019-05-30 | PXD010871 | Pride
Dia Prosit Retention time Predicted spectra Irt Machine learning Proteometools Spectral library Synthetic peptides Dda 
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