Oral sessions on artificial intelligence and mass spectrometry will be held at ASMS on June 7 from 8:30-10:30 am. Preview this session here.
From 8:30-10:30 am, Grand Ballroom C will host an oral session titled “Artificial Intelligence in MS Instruments and Applications.” Heather Desire, Session Chair, University of Kansas, will host the event to discuss the potential of artificial intelligence in how mass spectrometry is performed.
Starting at 8:30 am, the premiere talk will be moderated by Sivani Patel of Bristol-Myers Squibb, Princeton, New Jersey. Highlights how Patel and her team developed a predictive multiple reaction monitoring (MRM) model for high-throughput ADME analysis using Learning-to-Rank (LTR) techniques.
Next, at 8:50 a.m., Philip M. Rems of Thermo Fisher Scientific, San Jose, Calif., led a talk titled “Hodling When Ions Go to the Moon” to discuss how this tool might work. Focus on how you can help. Exceeds those used in mass spectrometry alone.
At 9:10 a.m., Melih Yilmaz of the University of Washington in Seattle, Washington, will talk about how her team used the Transformer model to guide inter-sequence translation from mass spectra to peptides.
This was followed by a 9:30 am talk led by Johrah Muhammad Musa, University of Waterloo, Waterloo, Ontario, Canada, on Peptide Identification Rate by Machine Learning with Peptide Spectral Matching, 2nd Place focus on improving
Subsequently, Damien B. Wilburn of Ohio State University, Columbus, Ohio, will lead the presentation at 9:50 am, discussing stochastic modeling of peptide chromatography using Chronologer NF, and discussing reversed-phase chemistry. provide new insights into
Finally, at 10:10, the talk will be led by Heinrich Luther, Institute for Applied Physics, Federal University of Defense Munich, Neubiberg, Germany. It focuses on real-time analysis and classification of aerosol particles using single-particle mass spectrometry and machine learning.
