Critical Assessment of Small Molecule Identification 2016: automated methods.
Journal article

Critical Assessment of Small Molecule Identification 2016: automated methods.

  • Schymanski EL Eawag: Swiss Federal Institute for Aquatic Science and Technology, Überlandstrasse 133, 8600, Dübendorf, Switzerland. emma.schymanski@eawag.ch.
  • Ruttkies C Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120, Halle, Germany.
  • Krauss M Department of Effect-Directed Analysis, UFZ: Helmholtz Centre for Environmental Research, Permoserstrasse 15, 04318, Leipzig, Germany.
  • Brouard C Department of Computer Science, Aalto University, Konemiehentie 2, 02150, Espoo, Finland.
  • Kind T West Coast Metabolomics Center and Genome Center, University of California Davis, 451 Health Sciences Drive, Davis, CA, 95616, USA.
  • Dührkop K Chair of Bioinformatics, Friedrich-Schiller-University, Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
  • Allen F Department of Computing Science, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
  • Vaniya A West Coast Metabolomics Center and Genome Center, University of California Davis, 451 Health Sciences Drive, Davis, CA, 95616, USA.
  • Verdegem D Metabolomics Expertise Center, Vesalius Research Center (VRC), VIB, KU Leuven - University of Leuven, 3000, Louvain, Belgium.
  • Böcker S Chair of Bioinformatics, Friedrich-Schiller-University, Jena, Ernst-Abbe-Platz 2, 07743, Jena, Germany.
  • Rousu J Department of Computer Science, Aalto University, Konemiehentie 2, 02150, Espoo, Finland.
  • Shen H Department of Computer Science, Aalto University, Konemiehentie 2, 02150, Espoo, Finland.
  • Tsugawa H RIKEN Center for Sustainable Resource Science (CSRS), 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan.
  • Sajed T Department of Computing Science, University of Alberta, Edmonton, AB, T6G 2E9, Canada.
  • Fiehn O West Coast Metabolomics Center and Genome Center, University of California Davis, 451 Health Sciences Drive, Davis, CA, 95616, USA.
  • Ghesquière B Metabolomics Expertise Center, Vesalius Research Center (VRC), VIB, KU Leuven - University of Leuven, 3000, Louvain, Belgium.
  • Neumann S Department of Stress and Developmental Biology, Leibniz Institute of Plant Biochemistry, Weinberg 3, 06120, Halle, Germany.
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  • 2017-11-01
Published in:
  • Journal of cheminformatics. - 2017
English BACKGROUND
The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest ( www.casmi-contest.org ) was held in 2016, with two new categories for automated methods. This article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluation of CASMI 2016 through to perspectives for future contests and small molecule annotation/identification.


RESULTS
The Input Output Kernel Regression (CSI:IOKR) machine learning approach performed best in "Category 2: Best Automatic Structural Identification-In Silico Fragmentation Only", won by Team Brouard with 41% challenge wins. The winner of "Category 3: Best Automatic Structural Identification-Full Information" was Team Kind (MS-FINDER), with 76% challenge wins. The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges. This success rate rose to 70% Top 1 ranks in Category 3, with candidates in the Top 10 in over 80% of the challenges. The machine learning and chemistry-based approaches are shown to perform in complementary ways.


CONCLUSIONS
The improvement in (semi-)automated fragmentation methods for small molecule identification has been substantial. The achieved high rates of correct candidates in the Top 1 and Top 10, despite large candidate numbers, open up great possibilities for high-throughput annotation of untargeted analysis for "known unknowns". As more high quality training data becomes available, the improvements in machine learning methods will likely continue, but the alternative approaches still provide valuable complementary information. Improved integration of experimental context will also improve identification success further for "real life" annotations. The true "unknown unknowns" remain to be evaluated in future CASMI contests. Graphical abstract .
Language
  • English
Open access status
gold
Identifiers
Persistent URL
https://sonar.ch/global/documents/210050
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