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Artificial intelligence in cancer target identification and drug discovery.

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收录情况: ◇ 统计源期刊 ◇ CSCD-C ◇ 卓越:领军期刊

机构: [1]College of Computer Science, Sichuan University, Chengdu 610065, China [2]Laboratory of Systems Tumor Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen 91052, Germany [3]Faculty of Computer Science and Control Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Room D513, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China [4]School of Computing, Ulster University, Belfast BT15 1ED, UK [5]Institute of Thoracic Oncology, Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu 610065, China [6]Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China [7]Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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摘要:
Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations. Second, we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. Finally, we showcase the applications of artificial intelligence approaches in cancer target identification and drug discovery. Taken together, the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer, thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.© 2022. The Author(s).

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出版当年[2022]版:
大类 | 1 区 医学
小类 | 1 区 生化与分子生物学 1 区 细胞生物学
最新[2023]版:
大类 | 1 区 医学
小类 | 1 区 生化与分子生物学 1 区 细胞生物学
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第一作者机构: [1]College of Computer Science, Sichuan University, Chengdu 610065, China
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通讯机构: [1]College of Computer Science, Sichuan University, Chengdu 610065, China [6]Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China [7]Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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