Author: Marcus Ludwig; Louis-Félix Nothias; Kai Dührkop; Irina Koester; Markus Fleischauer; Martin A. Hoffmann; Daniel Petras; Fernando Vargas; Mustafa Morsy; Lihini Aluwihare; Pieter C. Dorrestein; Sebastian Böcker
Title: ZODIAC: database-independent molecular formula annotation using Gibbs sampling reveals unknown small molecules Document date: 2019_11_16
ID: 03uonbrv_1
Snippet: For all ve datasets, we observe that ZODIAC outperforms SIRIUS, often substantially decreasing molecular formula annotation error rates (Fig. 1, left) . We rst consider the dendroides dataset, for which improvements are most distinctive: This dataset contains many larger compounds, and 75 % of the ground truth compounds have an m/z of 605 or higher ( Supplementary Fig. 6 )......
Document: For all ve datasets, we observe that ZODIAC outperforms SIRIUS, often substantially decreasing molecular formula annotation error rates (Fig. 1, left) . We rst consider the dendroides dataset, for which improvements are most distinctive: This dataset contains many larger compounds, and 75 % of the ground truth compounds have an m/z of 605 or higher ( Supplementary Fig. 6 ).
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