Predicting the decision making chemicals used for bacterial growth
Abstract
Predicting the contribution of media components to bacterial growth was first initiated by introducing machine learning to high-throughput growth assays. A total of 1336 temporal growth records corresponding to 225 different media, which were composed of 13 chemical components, were generated. The growth rate and saturated density of each growth curve were automatically calculated with the newly developed data processing program. To identify the...
Paper Details
Title
Predicting the decision making chemicals used for bacterial growth
Published Date
May 10, 2019
Journal
Volume
9
Issue
1
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