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iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning
Computer Science, Jingdezhen Ceramic Institute, Jingdezhen, China
Gordon Life Science Institute, Boston, MA 02478, USA
- 1 Computer Science, Jingdezhen Ceramic Institute, Jingdezhen, China
- 2 Gordon Life Science Institute, Boston, MA 02478, USA
Advances in Bioscience and Biotechnology·Volume 11 (2020)·Pages 153–159·Published 9 May 2020·DOI10.4236/abb.2020.115012
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Abstract
The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. To provide useful clues for developing antiviral drugs, information of anatomical therapeutic chemicals is vitally important. In view of this, a CNN based predictor called “iATC_Deep-mISF” has been developed. The predictor is particularly useful in dealing with the multi-label systems in which some chemicals may occur in two or more di fferent classes. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/iATC_Deep-mISF/ , which will become a very powerful tool for developing effective drugs to fight pandemic coronavirus and save the mankind of this planet.
KeywordsPandemic CoronavirusMulti-Label SystemAnatomical Therapeutic ChemicalsLearning at Deeper LevelFive-Steps Rule
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