Learning transferable deep convolutional neural networks for the classification of bacterial virulence factors
Motivation: Identification of virulence factors (VFs) is critical to the elucidation of bacterial pathogenesis and prevention of related infectious diseases. Current computational methods for VF prediction focus on binary classification or involve only several class(es) of VFs with sufficient sample...
محفوظ في:
| المؤلفون الرئيسيون: | , , , , |
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| التنسيق: | text |
| اللغة: | English |
| منشور في: |
Institutional Knowledge at Singapore Management University
2020
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sis_research/7038 https://ink.library.smu.edu.sg/context/sis_research/article/8041/viewcontent/btaa230.pdf |
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