AnalyzerPro is used worldwide by many talented and highly motivated scientists and it is always good to hear how they are using our product. We are grateful to those who have already shared their work with us and here you can see some of the interesting projects that our users are involved in. If you have an application which you would like to share with others, please do not hesitate to get in touch.
Metabolic profiling of breath analysis involves processing, alignment, scaling and clustering of thousands of features ex-tracted from Gas Chromatography Mass spectrometry (GC-MS) data from hundreds of participants.
For mass spectrometry (MS)-based metabolomics it is recommended to include the analysis of reference samples (preferably pooled study samples), as an added quality control (QC) measure at regular intervals throughout an analytical sequence.
Advances in Mass Spectrometry and MS data processing are enabling the analysis of micro samples and unknown components that were not previously observed. As the volume of information acquired from MS instruments increases, researchers are calling for more simple techniques to analyse the numerous components observed.
La cromatografía de gases-espectrometría de masas (GC-MS) es una poderosa técnica analítica para identificar, confirmar y cuantificar compuestos orgánicos en matrices complejas
Comparación automatizada de muestras de café por GC-MS con AnalyzerPro ASMS 2019.
Forensic laboratories routinely analyze samples collected from fire scenes for the presence of ignitable liquid residues (ILRs). ILRs are often recovered from fire debris using a passive heated headspace extraction, with adsorption of volatile components on active carbon followed by solvent or thermal desorption.
Gas chromatography-mass spectrometry (GC-MS) is a powerful analytical technique for identifying, confirming and quantifying organic compounds in complex matrices.
Comprehensive two-dimensional GC-MS is a powerful analytical tool that has evolved from technology used mainly in the R&D laboratory to a robust commercially available solution from several manufacturers. As the amount of data from these instruments can be overwhelming, we have developed AnalyzerPro XD as a vendor neutral 2D data processing solution for all chromatographic-MS data. This software uses chromatographic deconvolution and component reconstruction to isolate the components from each sample.
Metabolomics has a great potential in addressing the metabolic gap in microbe-host systems and expanding knowledge on the human gut microbial metabolism. Metabolomics as a field is the analysis and unbiased relative quantification of all metabolites in a biological sample. However in order to study the entire metabolome of a biological system, it is essential that most, if not all, of the metabolites present in the system in question are extracted and identified through analytical platforms.
To reduce the impact of non-biological variance introduced into untargeted metabolomics datasets by, among other factors, gradual changes in instrument performance, it is common practice to include the analysis of reference samples throughout an analytical sequence. There are few single software platforms for data processing, signal-correction and analysis/interpretation which are vendor neutral and support GC- and LC-MS data, and fewer implemented through a GUI. Here we present this software capability and have explored approaches for the validation of signal-corrected data.
Advances in mass spectrometry are enabling analysis of micro samples and unknown components that were not observable before. As the volume of information acquired from mass spectrometry increases, researchers are calling for simple techniques to analyze the numerous components observed, and as a result, there is a rise in demand for comprehensive analytical techniques including multiple classification analysis.
Advances in mass spectrometry are enabling analysis of micro samples and unknown components that were not observable before. As the volume of information acquired from mass spectrometry increases, researchers are calling for simple techniques to analyze numerous components observed, and as a result, there is a rise in demand for comprehensive analytical techniques including multiple classification analysis. In this work, we will introduce a new technique for non-target analysis, which combines comprehensive analysis using high resolution GC-TOFMS and unknown component analysis using soft ionization.