Identification of metabolic end goals by BOFdat Step 3. by Jean-Christophe Lachance (6619307)

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BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

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The three-step workflow for generating biomass objective functions from experimental data with BOFdat. by Jean-Christophe Lachance (6619307)

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BOFdat Step 2: Identifying and calculating the stoichiometric coefficients of coenzymes and inorganic ions. by Jean-Christophe Lachance (6619307)

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Performance metrics for ProSmith and previously published methods for DTA prediction on the random split of the Davis dataset. by Alexander Kroll (9304225)

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S1 Data - by Xinfu Pang (16713651)

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Basic flowchart of SCNs. by Xinfu Pang (16713651)

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Basic flowchart of Bagging. by Xinfu Pang (16713651)

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Time-dependent change of average temperature. by Xinfu Pang (16713651)

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Time-dependent change of average load. by Xinfu Pang (16713651)

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Forecasting process of Bagging-SCNs. by Xinfu Pang (16713651)

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Basic network structure of SCNs. by Xinfu Pang (16713651)

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Forecasting process of Bagging-SCNs. by Xinfu Pang (16713651)

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Short-term load forecasting model of SCNs. by Xinfu Pang (16713651)

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Replacing the final prediction layer of end-to-end trained Transformer Networks with gradient boosting models improves performance. by Alexander Kroll (9304225)

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ProSmith outperforms the ESP model in the prediction of enzyme-substrate pairs especially for molecules with limited representation in the test data. by Alexander Kroll (9304225)

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Performance metrics for all three trained gradient boosting models with different input vectors and for their combined weighted mean prediction. by Alexander Kroll (9304225)

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Coefficient of determination <i>R</i>² of ProSmith for different splitting scenarios of the Davis dataset. by Alexander Kroll (9304225)

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We divided the ESP test set into subsets according to the number of positive data points with the same small molecule in the training set. by Alexander Kroll (9304225)

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We divided the ESP test set into subsets according to the maximal sequence identity of an enzyme compared to all training enzymes. by Alexander Kroll (9304225)

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