基于生物学信息的神经网络预测药物反应。
Biologically Informed Neural Networks Predict Drug Responses.
机构信息
Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Childhood Cancer Data Lab, Alex's Lemonade Stand Foundation, Philadelphia, PA 19102, USA.
Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
出版信息
Cancer Cell. 2020 Nov 9;38(5):613-615. doi: 10.1016/j.ccell.2020.10.014. Epub 2020 Oct 22.
Deep neural networks often achieve high predictive accuracy on biological problems, but it can be hard to contextualize how and explain why predictions are made. In this issue, Kuenzi et al. model the sensitivity of cancers to drugs using deep neural networks with a hierarchical structure derived from the Gene Ontology.
深度神经网络在生物学问题上经常能达到很高的预测准确率，但很难理解其是如何做出预测的，也很难解释原因。在本期杂志中，Kuenzi 等人使用一种具有层次结构的深度神经网络模型来模拟癌症对药物的敏感性，该模型的层次结构来源于基因本体论。
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