e-Bitter: Bitterant Prediction by the Consensus Voting From the Machine-Learning Methods
In-silico bitterant prediction received the considerable attention due to the expensive and laborious experimental-screening of the bitterant. In this work, we collect the fully experimental dataset containing 707 bitterants and 592 non-bitterants, which is distinct from the fully or partially hypot...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2018-03-01
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| Series: | Frontiers in Chemistry |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/article/10.3389/fchem.2018.00082/full |