PXD022287 is an
original dataset announced via ProteomeXchange.
Dataset Summary
Title | A dataset for training/testing machine learning models of peptide feature detection: Human HELA LC-MSMS |
Description | We introduce MSTracer, a tool for peptide feature detection from MS1, which incorporates a machine-learning-combined scoring function based on peptide isotopic distribution and peptide intensity shape on the LC-MS map. By using Support Vector Regression (SVR), the quality of detected peptide features is remarkably improved. By utilising Neural Networks (NN), scores that indicate the quality of features are assigned for detected features as well. We use the Human HELA LC-MSMS dataset to train and test the results and compare with MaxQuant, OpenMS, and Dinosaur. |
HostingRepository | PRIDE |
AnnounceDate | 2024-10-22 |
AnnouncementXML | Submission_2024-10-22_05:23:02.803.xml |
DigitalObjectIdentifier | https://dx.doi.org/10.6019/PXD022287 |
ReviewLevel | Peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Supported dataset by repository |
PrimarySubmitter | Xiangyuan Zeng |
SpeciesList | scientific name: Homo sapiens (Human); NCBI TaxID: 9606; |
ModificationList | iodoacetamide derivatized amino-terminal residue |
Instrument | Orbitrap Fusion |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
0 | 2020-11-02 01:42:03 | ID requested | |
1 | 2021-06-17 20:20:52 | announced | |
2 | 2023-11-14 08:52:54 | announced | 2023-11-14: Updated project metadata. |
⏵ 3 | 2024-10-22 05:23:03 | announced | 2024-10-22: Updated project metadata. |
Publication List
Keyword List
ProteomeXchange project tag: deep learning, benchmarking, machine learning |
submitter keyword: Human, LC-MS/MS |
Contact List
Bin Ma |
contact affiliation | University of Waterloo |
contact email | bin.ma@uwaterloo.ca |
lab head | |
Xiangyuan Zeng |
contact affiliation | University of Waterloo |
contact email | x25zeng@uwaterloo.ca |
dataset submitter | |
Full Dataset Link List
Dataset FTP location
NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2021/06/PXD022287 |
PRIDE project URI |
Repository Record List
[ + ]
[ - ]
- PRIDE
- PXD022287
- Label: PRIDE project
- Name: A dataset for training/testing machine learning models of peptide feature detection: Human HELA LC-MSMS