Complexity to Clarity: Transforming chromatographic data into usable results | LabRulez GCMS

Complexity to Clarity: Transforming chromatographic data into usable results

ZÁZNAM | Proběhlo Út, 22.9.2020
V tomto webináři Vám představujeme ChromCompare+, výkonnou, ale intuitivní platformu, která Vám umožní získat maximum cenných informací z komplexních chromatografických dat a transformovat je na výsledky.
Markes International: Complexity to Clarity - Transforming chromatographic data into usable results

Markes International: Complexity to Clarity - Transforming chromatographic data into usable results

Constant advances in sample introduction, chromatographic separation and detection by mass spectrometry mean we can now gain greater insight in to sample composition than ever before, but the question remains “what am I going to do with all of this data?”

In this webinar, we introduce ChromCompare+, a powerful, yet intuitive, platform allowing you to extract maximum valuable information from complex chromatograms and transform this data into usable results to drive your business forward.

With much of its development driven by input from our extensive user base, ChromCompare+ has evolved into a comprehensive platform supporting a range of file formats, allowing you to improve your 1D and 2D GC-MS systems and accelerate decision-making.

Register now to see this exciting new software in action across a range of real-world applications – allowing you to discover more and deliver more in fragrance profiling, food authenticity and biomarker studies.

Who should attend?

GC-MS and GC×GC-MS users who need:

  • To make data processing simpler, more enjoyable, and more productive
  • To find key differences between complex chromatograms
  • To make fast decisions that impact business success

Learning outcomes

  • Learn how to use chemometrics to spot the difference between complex samples, without having to be a statistics expert
  • Find out how alignment and raw data workflows leave no trace peaks overlooked
  • Hear how prediction models can be used to quickly and accurately classify future samples
SepSolve Analytical
 

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