Prediction of peptide mass spectral libraries with machine learning
J Cox - Nature Biotechnology, 2023 - nature.com
The recent development of machine learning methods to identify peptides in complex mass
spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods …
spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods …
Deep learning in proteomics
Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich
science. Protein sequences and structures are comprehensively catalogued in online …
science. Protein sequences and structures are comprehensively catalogued in online …
The ProteomeXchange consortium in 2020: enabling 'big data'approaches in proteomics
EW Deutsch, N Bandeira, V Sharma… - Nucleic acids …, 2020 - academic.oup.com
The ProteomeXchange (PX) consortium of proteomics resources (http://www.
proteomexchange. org) has standardized data submission and dissemination of mass …
proteomexchange. org) has standardized data submission and dissemination of mass …
A streamlined platform for analyzing tera-scale DDA and DIA mass spectrometry data enables highly sensitive immunopeptidomics
Integrating data-dependent acquisition (DDA) and data-independent acquisition (DIA)
approaches can enable highly sensitive mass spectrometry, especially for …
approaches can enable highly sensitive mass spectrometry, especially for …
An introduction to advanced targeted acquisition methods
M van Bentum, M Selbach - Molecular & Cellular Proteomics, 2021 - ASBMB
Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring
(PRM) enables fast and sensitive detection of a preselected set of target peptides. However …
(PRM) enables fast and sensitive detection of a preselected set of target peptides. However …
Early Pleistocene enamel proteome from Dmanisi resolves Stephanorhinus phylogeny
The sequencing of ancient DNA has enabled the reconstruction of speciation, migration and
admixture events for extinct taxa. However, the irreversible post-mortem degradation of …
admixture events for extinct taxa. However, the irreversible post-mortem degradation of …
Reproducibility, specificity and accuracy of relative quantification using spectral library-based data-independent acquisition
K Barkovits, S Pacharra, K Pfeiffer, S Steinbach… - Molecular & Cellular …, 2020 - ASBMB
Currently data-dependent acquisition (DDA) is the method of choice for mass spectrometry-
based proteomics discovery experiments, but data-independent acquisition (DIA) is steadily …
based proteomics discovery experiments, but data-independent acquisition (DIA) is steadily …
MS2Rescore: data-driven rescoring dramatically boosts immunopeptide identification rates
A Declercq, R Bouwmeester, A Hirschler… - Molecular & Cellular …, 2022 - ASBMB
Immunopeptidomics aims to identify major histocompatibility complex (MHC)-presented
peptides on almost all cells that can be used in anti-cancer vaccine development. However …
peptides on almost all cells that can be used in anti-cancer vaccine development. However …
Oktoberfest: Open‐source spectral library generation and rescoring pipeline based on Prosit
Abstract Machine learning (ML) and deep learning (DL) models for peptide property
prediction such as Prosit have enabled the creation of high quality in silico reference …
prediction such as Prosit have enabled the creation of high quality in silico reference …
Updated MS²PIP web server supports cutting-edge proteomics applications
Interest in the use of machine learning for peptide fragmentation spectrum prediction has
been strongly on the rise over the past years, especially for applications in challenging …
been strongly on the rise over the past years, especially for applications in challenging …