Compound Discoverer™ Software

Streamline and customize high-resolution accurate-mass data analysis for small molecule workflows with Thermo Scientific™ Compound Discoverer™ software. Compound Discoverer software simplifies and reduces processing, enabling you to go from data to insights faster. Leverage easy to use pre-built workflow templates or fully customizable node-based workflows, integrated compound identification capabilities, and statistical analysis tools for streamlined data analyses to deliver confident results to drive your decision making.

Know more unknowns

• Identify compounds using automatic multiple database and spectral library search tools including mzCloud™, Chemspider™, KEGG, and BioCyc, and local database search tools such as the mzVault™ spectral library or mass lists.
• Access the latest "auto-processed" mzCloud libraries and utilize both DIA and DDA scans for searching.
• Determine elemental composition using high resolution fine isotopes, MS/MS, and MSⁿ data.
• Enables data analysis of high resolution, accurate mass Orbitrap mass spectrometers coupled to either liquid chromatography (LC) or gas chromatography (GC) instrumentation.

Workflow flexibility to match analytical requirements
Compound Discoverer software offers complete flexibility, making it easy to assemble a workflow that matches the analytical requirements of your analysis.

• Workflows are modular and assembled from a suite of advanced algorithms (nodes).
• Customizable workflow templates for different applications are included with the software for ease-of-use.
• Workflows can be enhanced with custom nodes to meet the needs of your most challenging research.

Advanced data processing and visualization

• Increase certainty using multi-factorial Peak Quality factors to reveal, identify, and quantify more compounds with confidence.
• Biological pathway analysis with high quality data processing and statistical analysis—support for stable isotope labeling (“flux analysis”) workflows to analyze differences in samples.
• Find real differences between sample sets with heat map-like tables, interactive PCA, partial least squares discriminant analysis (PLS-DA), etc.
• Visualization of spectral trees along with fragmentation annotations and mzLogic algorithm for ranking chemical database hits using spectral library similarities for structural elucidation.
• Molecular networks to explore relationships between compounds.