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Tytus Mak is a statistician in the Mass Spectrometry Data Center at the National Institute of Standards and Technology (NIST). His research focuses on developing machine learning approaches for analyzing big datasets generated by high-throughput biomolecular analysis platforms including metabolomics, glycomics and proteomics. He received his B.S. in electrical and computer engineering at Cornell University and his Ph.D. in bioinformatics and tumor biology at Georgetown University. He is also an avid martial artist and spends his free time practicing karate and kenjutsu.
When one thinks of mass spectral libraries — well, let’s be honest here, the very idea of mass spectral libraries will never cross most people’s minds, even