Exploring Agilent Software for Machine Learning and Classification with High Resolution Liquid Chromatography Mass Spectrometry Data and Experimental Design Ideas to Maximize Success

Datasets are ever increasing in complexity and sophistication as scientists tackle even more challenging problems. This scientific complexity demands new approaches and advanced tools for analysis. Leading these innovative approaches is the introduction of machine learning and classification techniques for the analysis of high-resolution liquid chromatography mass spectrometry datasets.

Here we will explore different application spaces for these techniques in food, environment and the life sciences with the easy to use MassHunter Classifier software that can directly read raw data and make predictions. Further to make the most of these innovations we will discuss practical experimental design considerations to maximize machine learning and classification outputs.

For Research Use Only. Not for use in diagnostic procedures.

Presenter: Dan Cuthbertson (Field Application Scientist, Agilent Technologies, Inc.)

Daniel Cuthbertson is a Field Application Scientist at Agilent Technologies. He is recognized internationally for his consulting for ‘omics applications and chemometric applications in food and the environment. He has a strong background in multivariate statistics, experimental design, and is an expert in LCMS method development. Dan is passionate about mass spectrometry education and teaches courses on statistical analysis of mass spectrometry data. He received his Ph.D. at Washington State University where he worked on food metabolomics and natural product structure elucidation. At home he enjoys gardening, mushroom hunting and his time as a NCAA soccer referee.

Presenter: Karen Yannell (LC/MS Application Engineer, Agilent Technologies, Inc.)

Karen E. Yannell is a LC/MS Application Engineer at Agilent Technologies. She is an expert in small molecule high throughput analysis by triple quadrupole (TQ) and quadrupole time-of-flight (QTOF) mass spectrometry for applied markets. Her recent work has focused on developing routine Q-TOF workflows for both expert and non-expert users alike. Previously, Karen worked on forensic, metabolomics, and biomarker discovery applications with ambient ionization sources. She received her PhD in Analytical Chemistry from Purdue University where studied under the advisement of Prof. R. Graham Cooks. Outside of the laboratory, she enjoys cooking unique dishes and hiking along the beach with her dog.