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Machine Learning Empowered Drug Screen
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Department of Computer Science, Shantou University, Shantou 515063, China
Dr. Jiaqi Wang
School of Pharmaceutical Sciences, Sun Yat-sen University, Shenzhen 518107, China
Dr. Youyi Song
Centre for Smart Health, The Hong Kong Polytechnic University, Hong Kong, China
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Machine Learning Empowered Drug Screen

Abstract submission deadline
closed (30 June 2024)
Manuscript submission deadline
31 August 2024
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Topic Information

Dear Colleagues,

Drug design is a lengthy, costly, difficult, and inefficient process in spite of advances in biotechnology and the understanding of biological systems. Finding efficient drug pathways is crucial in the fight against future outbreaks, and much effort has been devoted to it. Computer-aided drug design (CADD) plays a vital role in accelerating the discovery of potential lead compounds and the optimization of their structure for the following pharmacological tests. In CADD, machine learning is widely used to train a model to predict the target properties including their potency and toxicity. Thus, machine learning methods are required to better accelerate the design of drugs. In this Special Issue on “Machine Learning-Empowered Drug Screen”, we will discuss various aspects of drug screen using machine learning methods.

Dr. Teng Zhou
Dr. Jiaqi Wang
Dr. Youyi Song
Topic Editors

Keywords

  • drug screen
  • machine learning
  • bioinformatics
  • data science
  • CADD

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Algorithms
algorithms 		1.8 4.1 2008 15 Days CHF 1600 Submit
Big Data and Cognitive Computing
BDCC 		3.7 7.1 2017 18 Days CHF 1800 Submit
BioMedInformatics
biomedinformatics 		- 1.7 2021 21.3 Days CHF 1000 Submit
Information
information 		2.4 6.9 2010 14.9 Days CHF 1600 Submit
Mathematics
mathematics 		2.3 4.0 2013 17.1 Days CHF 2600 Submit

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Published Papers (3 papers)

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