Single-Cell Techniques and Deep Learning in Predicting Drug Response.
Single-Cell Techniques and Deep Learning in Predicting Drug Response.
复制标题
单细胞技术和深度学习在药物反应预测中的应用
DOI:
10.1016/j.tips.2020.10.004
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发表时间:
2020-12
影响因子:
13.8
通讯作者:
Ma Q
中科院分区:
文献类型:
--
作者:
Wu Z;Lawrence PJ;Ma A;Zhu J;Xu D;Ma Q
Rapidly developing single-cell sequencing analyses produce more comprehensive profiles of genomic, transcriptomic, and epigenomic heterogeneity present in tumor subpopulations than traditional bulk sequencing analyses. Moreover, single-cell techniques allow a tumor’s response to drug exposure to be more thoroughly investigated. Deep learning models have successfully extracted features from complex bulk sequence data to predict drug responses. Here, we review recent innovations in single-cell technologies and deep learning-based approaches related to drug sensitivity predictions. We believe that using insights from bulk sequence data, deep transfer learning would facilitate the application of single-cell data to train superior deep learning-based drug prediction models.
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影响因子:
50.3
作者:
Hinohara K;Wu HJ;Vigneau S;McDonald TO;Igarashi KJ;Yamamoto KN;Madsen T;Fassl A;Egri SB;Papanastasiou M;Ding L;Peluffo G;Cohen O;Kales SC;Lal-Nag M;Rai G;Maloney DJ;Jadhav A;Simeonov A;Wagle N;Brown M;Meissner A;Sicinski P;Jaffe JD;Jeselsohn R;Gimelbrant AA;Michor F;Polyak K
通讯作者:
Polyak K
影响因子:
82.9
作者:
Fairfax BP;Taylor CA;Watson RA;Nassiri I;Danielli S;Fang H;Mahé EA;Cooper R;Woodcock V;Traill Z;Al-Mossawi MH;Knight JC;Klenerman P;Payne M;Middleton MR
通讯作者:
Middleton MR
影响因子:
2.7
作者:
Chiu, Yu-Chiao;Chen, Hung-I Harry;Chen, Yidong
通讯作者:
Chen, Yidong
影响因子:
5.9
作者:
Goldstein, Leonard D.;Chen, Ying-Jiun J.;Seshagiri, Somasekar
通讯作者:
Seshagiri, Somasekar
影响因子:
64.5
作者:
Dixit, Atray;Pamas, Oren;Li, Biyu;Chen, Jenny;Fulco, Charles P.;Jerby-Amon, Livnat;Marjanovic, Nemanja D.;Dionne, Danielle;Burks, Tyler;Raychowdhury, Raktima;Adamson, Britt;Norman, Thomas M.;Lander, Eric S.;Weissman, Jonathan S.;Friedman, Nir;Regev, Aviv
通讯作者:
Regev, Aviv