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https://doi.org/10.1093/bioinformatics/btw186

has been cited by the following article:

• TITLE: iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning

  AUTHORS: Zhe Lu, Kuo-Chen Chou

  KEYWORDS: Pandemic Coronavirus, Multi-Label System, Anatomical Therapeutic Chemicals, Learning at Deeper Level, Five-Steps Rule

  JOURNAL NAME: Advances in Bioscience and Biotechnology, Vol.11 No.5, May 11, 2020

  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 different 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.