A discussion with Thomas Durant and Edward Lee about recent advances in machine learning (ML) for mass spectrometry (MS) data analysis.
We will be talking with Thomas Durant and Edward Lee about recent advances in machine learning (ML) for mass spectrometry (MS) data analysis. The primary focus will be the alignment of these two fields (ML and MS) and how this offers a promising synergy that can be used to optimize workflows, improve result quality, and enhance our understanding of high-dimensional datasets, as well as their inherent relationship with disease biology. We will also dig deeper to understand a basic overview of ML and an ML-based experiment. Overall, we will have a opportunity go through the fundamental principles of supervised ML, outline the steps that are classically involved in an ML-based experiment, and discuss the purpose of good ML practice in the context of a binary MS classification problem.