首页|Data on Machine Learning Reported by Yannek Nowatzky and Colleagues (Machine lea rning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods)
Data on Machine Learning Reported by Yannek Nowatzky and Colleagues (Machine lea rning methods for compound annotation in non-targeted mass spectrometry-A brief overview of fingerprinting, in silico fragmentation and de novo methods)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting from Berlin, Germany, by News Rx journalists, research stated, “Non-targeted screenings (NTS) are essential to ols in different fields, such as forensics, health and environmental sciences. N TSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance-based met hods.” The news correspondents obtained a quote from the research, “As the identificati on of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, b oth the diversity of mass spectral signals and the sheer quantity of different M L tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field. In this work, we illustrate which ML-based methods are available for compound annotation in non-targeted MS experiments and provide a nuanced comparison of the ML models used in MS data an alysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research.”
BerlinGermanyEuropeCyborgsEmergi ng TechnologiesMachine Learning
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