PXD059666 is an
original dataset announced via ProteomeXchange.
Dataset Summary
| Title | Hepatocyte Proteome Destabilization and Novel Targets for PFASs Unveiled through Combined Thermal Proteome Profiling and Deep Transfer Learning |
| Description | TPP-CCR (Thermal proteome profiling with compound concentration range TPP-CCR) identified key protein targets for three representative PFASs and a benchmark sample of staurosporine. |
| HostingRepository | PRIDE |
| AnnounceDate | 2026-05-13 |
| AnnouncementXML | Submission_2026-05-13_13:36:58.043.xml |
| DigitalObjectIdentifier | |
| ReviewLevel | Peer-reviewed dataset |
| DatasetOrigin | Original dataset |
| RepositorySupport | Unsupported dataset by repository |
| PrimarySubmitter | Zimeng Wu |
| SpeciesList | scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606; |
| ModificationList | No PTMs are included in the dataset |
| Instrument | Orbitrap Exploris 480 |
Dataset History
| Revision | Datetime | Status | ChangeLog Entry |
| 0 | 2025-01-11 04:22:26 | ID requested | |
| ⏵ 1 | 2026-05-13 13:36:58 | announced | |
Publication List
Keyword List
Contact List
| Zhiqiang Fu |
| contact affiliation | Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology |
| contact email | iswuzimeng@163.com |
| lab head | |
| Zimeng Wu |
| contact affiliation | 18222593531 |
| contact email | iswuzimeng@163.com |
| 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/2026/05/PXD059666 |
| PRIDE project URI |
Repository Record List
[ + ]
[ - ]
- PRIDE
- PXD059666
- Label: PRIDE project
- Name: Hepatocyte Proteome Destabilization and Novel Targets for PFASs Unveiled through Combined Thermal Proteome Profiling and Deep Transfer Learning