PANOMIX LCMS annotation landscape

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The panorama of non-targeted metabolite detection in the PANOMIX Laboratory, the result data comes from the R&D test results of about 20,000 PANOMIX metabolite standards library in 2024, range from the secondary metabolites of plant natural products to the endogenous metabolites common to plants and animals. Only represents the ability of non-targeted substances to be detected under the conditions of the PANOMIX laboratory, and provided to you as a reference for you to choose our scientific research service for the LC-MS detection and data analysis services of your sample data.

Help: Click the scatter to jump to the metabolite detection information detail page, click the legend on the right side of the chart to filter the data, use the mouse wheel to zoom in or out of the scatter chart, and drag and drop the mouse to adjust the viewing angle.
Click on the link below to get a list of the top 500 metabolites that can be detected stably in our different annotation workflow, if you need to get the full metabolite list, you can contact us through email market@bionovogene.com for academic cooperation to get it for free:

  • OTCML: It is mainly for the annotation of about 1000 kinds of plant Chinese medicine and insect and animal Chinese medicine metabolites derived from traditional Chinese medicine, which is suitable for the analysis of traditional Chinese medicine raw materials and traditional Chinese medicine preparations.
  • plant: Annotation of the metabolites (primary metabolites and secondary metabolites) of plant origin, and is suitable for the analysis of plant tissues, or the analysis of body fluids and excreta of herbivores.
  • natural_products: Annotation of the secondary metabolites (such as toxins, alkaloids, hormones, antibiotics) in microorganisms, animals and plants, and is suitable for data analysis of sample types such as animal tissues, plant tissues, fermentation broths, etc.
  • endogenous: Annotation of the primary metabolites necessary for life activities, and is suitable for the data analysis of all types of biological samples (e.g., animal and plant tissues, cell contents).
  • feces: Annotation of the common metabolites in animal fecal samples.
  • urine: Annotation of the common metabolites in animal urine samples.
  • blood: Annotation of the metabolites commonly found in animal blood samples.
  • lipidomics: Annotation of the lipids metabolites in various biological samples.