Python code for Model 2 used to predict FAZ area from FAZ length measurements. by Taku Toyama (102864)

“…<p>Python code for Model 2 used to predict FAZ area from FAZ length measurements.…”

Python codes for ML-Pain-MEDD by Vivian Salama (13001475)

The optimal ProSmith models combine predictions based on the multimodal Transformer Network with predictions based on separate numerical representations of proteins and small molec... by Alexander Kroll (9304225)

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PHOTONAI explorer. by Ramona Leenings (11167294)

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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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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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Python code for Model 1 used to predict FAZ length from B-scan OCT images. by Taku Toyama (102864)

“…<p>Python code for Model 1 used to predict FAZ length from B-scan OCT images.…”

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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ProSmith outperforms previous models in the prediction of Michaelis constants <i>K</i>_M especially for enzymes not highly similar to proteins in the training set. by Alexander Kroll (9304225)

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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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Five Operator Lattice Simulation by James McDaniel (22522571)

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PCA_WNN model by Dongmei Wang (14179892)

“…<p>This is a python code about the neural network model for predicting kinetic data during treadmill running.…”

Python code for Model 3 used to convert FAZ area from pixels to mm². by Taku Toyama (102864)

Performance metrics for ProSmith and ESP for the prediction of enzyme-substrate pairs. by Alexander Kroll (9304225)

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Python script of the PREDICATE tool written in a Jupyter Notebook format. by Nantia Leonidou (14833068)

For accurate DTA predictions, ProSmith requires training on identical drugs but not on similar proteins. by Alexander Kroll (9304225)

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Enzyme-substrate pair predictions improve with increasing substrate similarity compared to training substrates. by Alexander Kroll (9304225)

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Comparison of SDR predicted by ITC measurement model and variance function. by Xiujie Ge (6831833)

Performance metrics for ProSmith and previously published methods for DTA prediction for different splitting scenarios. by Alexander Kroll (9304225)

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Drug-target affinity predictions improve with increasing drug similarity score compared to the training drugs. by Alexander Kroll (9304225)

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