Research and Reports in Medical Sciences

Department of Biology and Biological Engineering, South China University of Technology, Guangzhou, China

Publications

• Mini Review   
  Deep Cancer Map: A Flexible Profound Learning Stage for Target and Cell-Based Anticancer Medication Disclosure
  Author(s): Ling Wang*
  
  Finding new anticancer medications has been generally concerned and stays an open test. Both phenotypic-based experimental screening and target-based experimental screening are common approaches to the discovery of anticancer drugs. Both of these approaches are time-consuming, labor-intensive, and expensive. In this review, we gathered 485,900 mixtures including in 3,919,974 bioactivity records against 426 anticancer targets and 346 disease cell lines from scholastic writing, as well as 60 growth cell lines from NCI-60 board. The FP-GNN deep learning method was then used to create a total of 832 classification models, including 426 target- and 406 cell-based predictive models, to predict the inhibitory activity of compounds against targets and tumor cell lines. The FP-GNN models outperform conventional machine learning and deep learning in terms of overall pred.. Read More»
  DOI: 10.37421/2952-8127.2023.7.111

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