title: Winners of CASMI2013: Automated Tools and Challenge Data.
abstract: CASMI (Critical Assessment of Small Molecule Identification) is a contest in which participants identify the molecular formula and chemical structure of challenging molecules using blind mass spectra as the challenge data. Seven research teams participated in CASMI2013. The winner of CASMI2013 was the team of Andrew Newsome and Dejan Nikolic, the University of Illinois at Chicago, IL, USA. The team identified 15 among 16 challenge molecules by manually interpreting the challenge data and by searching in-house and public mass spectral databases, and chemical substance and literature databases. MAGMa was selected as the best automated tool of CASMI2013. In some challenges, most of the automated tools successfully identified the challenge molecules, independent of the compound class and magnitude of the molecular mass. In these challenge data, all of the isotope peaks and the product ions essential for the identification were observed within the expected mass accuracy. In the other challenges, most of the automated tools failed, or identified solution candidates together with many false-positive candidates. We then analyzed these challenge data based on the quality of the mass spectra, the dissociation mechanisms, and the compound class and elemental composition of the challenge molecules.
authors.affiliation: Graduate School of Information Science, Nara Institute of Science and Technology.
authors.forename: Takaaki
authors.initials: T
authors.lastname: Nishioka
authors.affiliation: Research Center for Medical and Dental Sciences, Tokyo Medical and Dental University.
authors.forename: Takeshi
authors.initials: T
authors.lastname: Kasama
authors.affiliation: National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology (AIST).
authors.forename: Tomoya
authors.initials: T
authors.lastname: Kinumi
authors.affiliation: Graduate School of Agriculture, Shinshu University.
authors.forename: Hidefumi
authors.initials: H
authors.lastname: Makabe
authors.affiliation: Graduate School of Information Science and Technology, Osaka University.
authors.forename: Fumio
authors.initials: F
authors.lastname: Matsuda
authors.affiliation: Innovation Center for Medical Redox Navigation, Kyushu University.
authors.forename: Daisuke
authors.initials: D
authors.lastname: Miura
authors.affiliation: Graduate School of Agriculture, Kyoto University.
authors.forename: Masahiro
authors.initials: M
authors.lastname: Miyashita
authors.affiliation: Collaboration Promotion Unit, RIKEN Global Research Cluster.
authors.forename: Takemichi
authors.initials: T
authors.lastname: Nakamura
authors.affiliation: College of Pharmaceutical Sciences, Ritsumeikan University.
authors.forename: Ken
authors.initials: K
authors.lastname: Tanaka
authors.affiliation: Osaka City Institute of Public Health and Environmental Sciences.
authors.forename: Atsushi
authors.initials: A
authors.lastname: Yamamoto
keywords: automated identification; challenge molecules; data quality; mass spectrometry; metabolomics
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