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Bin Li and Warren J. Gallin Department of Biological Sciences University of Alberta

Prediction of Half Activation Voltages of Voltage-gated Potassium Channels Based on Amino Acid Sequences Using Machine Learning. Bin Li and Warren J. Gallin Department of Biological Sciences University of Alberta Edmonton, Canada. VKC. Data Processing. Basic Learning. Training data:

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Bin Li and Warren J. Gallin Department of Biological Sciences University of Alberta

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  1. Prediction of Half Activation Voltages of Voltage-gated Potassium Channels Based on Amino Acid Sequences Using Machine Learning Bin Li and Warren J. Gallin Department of Biological Sciences University of Alberta Edmonton, Canada

  2. VKC Data Processing Basic Learning Training data: 58 VKC sequences -296 residues (features) each Class: published Va values Wrapper KNN classifier Comparison Matrix Outlier Selection Filter http://vkcdb.biology.ualberta.ca Training set Construction of classifier

  3. * * Q/E * A/S/V * * R/K * * KNN classifier Feature selection  wrapper BLOSUM62 • Outlier selection Mathematics Biology? Machine learning may not provide definitive answers to biological problems, but it help propose new hypotheses for experimental tests.

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