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MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics.

, , , , , , , , , and . J. Cheminformatics, (2015)

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MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics., , , , , , , , , and . J. Cheminformatics, (2015)Acceleration Strategies to Enhance Metabolic Ensemble Modeling Performance., , , and . Biophysical journal, 113 (5): 1150--1162 (Sep 5, 2017)Bayesian inference of metabolic kinetics from genome-scale multiomics data., , , , and . PLoS Comput. Biol., (2019)Predicting novel substrates for enzymes with minimal experimental effort with active learning., , , , , and . Metabolic engineering, (November 2017)Toward design-based engineering of industrial microbes, , and . Current Opinion in Microbiology, 13 (3): 255--262 (Jun 11, 2010)Efficient searching and annotation of metabolic networks using chemical similarity., , , and . Bioinform., 31 (7): 1016-1024 (2015)CellSort: a support vector machine tool for optimizing fluorescence-activated cell sorting and reducing experimental effort., , , and . Bioinform., 33 (6): 909-916 (2017)Nucleotide-time alignment for molecular recorders., , , , and . PLoS Comput. Biol., (2017)Pickaxe: a Python library for the prediction of novel metabolic reactions., , , and . BMC Bioinform., 24 (1): 106 (December 2023)MINE 2.0: enhanced biochemical coverage for peak identification in untargeted metabolomics., , , and . Bioinform., 38 (13): 3484-3487 (2022)