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Thermo Fisher
Q Exactive Orbitrap

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Lab Devices
Thermo Fisher
Q Exactive Orbitrap

Analyze Q Exactive Orbitrap Mass Spectrometer data with AI

Identify and quantify molecules via high-resolution mass spectrometry

Mass Analyzer: Orbitrap with <5 ppm accuracy

Resolution: Up to 140,000

MS Capability: Full MS and MS/MS (tandem)

Ionization: Polarity switching

Data Export: RAW files, CSV results

Get Started For Free Fully compatible with Sourcetable

Quick Start Integration

Get your Q Exactive Orbitrap data into Sourcetable in 3 simple steps

Export Data

Export identified features and quantification data from your Q Exactive via Xcalibur/Proteome Discoverer to CSV
Upload to Sourcetable

Import your high-resolution mass spectrometry data into Sourcetable for comprehensive analysis
Start Analysis

Perform automated compound identification, accurate mass analysis, and label-free quantification

File Format Compatibility

Optimized for high-resolution mass spectrometry with compound identification and quantitative proteomics

.csv

Raw Data

Full Support Compound identification, accurate mass determination, peak intensities, database search results

.raw

Processing Required Requires processing via third-party tools before import

Pre-built Analysis Workflows

Advanced workflows for proteomics, metabolomics, and high-resolution mass spectrometry analysis

🔬

Compound Identification

High-resolution mass spectrometry for accurate compound identification

Mass Spectrometry Compound ID Accurate Mass Database Search

🧬

Proteomics Analysis

Label-free quantification and protein identification

Proteomics Label-Free Protein ID Quantification

📈

Metabolomics Studies

Untargeted metabolomics and small molecule analysis

Metabolomics Small Molecules Untargeted Analysis

Technical Requirements

Software Dependencies

Q Exactive Orbitrap High-resolution LC-MS/MS system
Control Software Xcalibur/Proteome Discoverer
File Export Format CSV (processed), RAW (native)
Applications Proteomics, metabolomics, pharmaceutical research

Sourcetable Libraries

Data Processing pandas, numpy
Statistical Analysis scipy, statsmodels
Visualization matplotlib, plotly
MS Analysis pyopenms, scikit-learn

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