Proteomics

Proteomics Services — Discovery to Validation

DIA, PTM, 4D and PRM targeted proteomics: with Orbitrap high-resolution mass spectrometry as the core platform, projects run from large-scale discovery to targeted candidate validation as a closed loop, delivering protein quantification matrices and bioinformatics reports.

4
Service lines
SERVICE LINES
3–5 wks
Typical turnaround
TYPICAL TURNAROUND
Orbitrap
High-resolution MS
HRMS PLATFORM

Service Workflow

SERVICE WORKFLOW
1
Sample intake
QC · protein assay
2
Digestion
reduction/alkylation · digestion
3
MS acquisition
high-resolution LC-MS/MS
4
Database search
search · quantification
5
Report delivery
matrix + bioinformatics
Note: standard proteomics projects take 3–5 weeks depending on sample number and analysis depth; key milestones (sample QC, LC-MS/MS completion) are proactively synced.:

FAQ

FAQ
How long does a Proteomics project take?
Standard proteomics projects take 3-5 weeks depending on sample number and analysis depth; key milestones (sample QC, LC-MS/MS completion) are proactively synced with you.
How should proteomics samples be stored and shipped?
Store at -80°C and ship on dry ice; avoid repeated freeze-thaw cycles. Protease inhibitors are recommended for protein samples. A tailored Sample Collection Guide is provided before shipping.
How can DIA proteomics results be validated?
We recommend PRM targeted proteomics for candidate validation (antibody-free, highly reproducible), or classic assays such as Western Blot and ELISA, forming a "discovery → validation" closed loop.
What samples do you need for Proteomics?
Cells ≥1×10⁶, tissue ≥50 mg, serum/plasma ≥50 μL, FFPE ≥4 sections (5 μm). Protein samples tolerate freeze–thaw poorly — aliquot so each tube is thawed once; for PTM work include matched controls and avoid phosphate buffers. See Technical Resources → Sample Guide.

Delivery timing: sample shipping, customs declaration and similar steps may extend turnaround; actual project timelines prevail.

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Free study design · Interactive execution · In-depth data interpretation

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