Predicting tumor cell line response to drug pairs with deep learning

被引：0
|
作者：
Fangfang Xia
Maulik Shukla
Thomas Brettin
Cristina Garcia-Cardona
Judith Cohn
Jonathan E. Allen
Sergei Maslov
Susan L. Holbeck
James H. Doroshow
Yvonne A. Evrard
Eric A. Stahlberg
Rick L. Stevens
机构：
[1] Computing,
[2] Environment and Life Sciences,undefined
[3] Argonne National Laboratory,undefined
[4] Computation Institute,undefined
[5] The University of Chicago,undefined
[6] Center for Nonlinear Studies,undefined
[7] Los Alamos National Laboratory,undefined
[8] Computer Science,undefined
[9] Los Alamos National Laboratory,undefined
[10] Computation Directorate,undefined
[11] Lawrence Livermore National Laboratory,undefined
[12] Department of Bioengineering and Carl R. Woese Institute for Genomic Biology,undefined
[13] University of Illinois at Urbana-Champaign,undefined
[14] Developmental Therapeutics Branch,undefined
[15] National Cancer Institute,undefined
[16] Data Science and Information Technology Program,undefined
[17] Frederick National Laboratory for Cancer Research,undefined
来源：
BMC Bioinformatics | / 19卷
关键词：
Machine learning; Deep learning; Combination therapy; in silico drug screening;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [1] Predicting tumor cell line response to drug pairs with deep learning
    Xia, Fangfang
    Shukla, Maulik
    Brettin, Thomas
    Garcia-Cardona, Cristina
    Cohn, Judith
    Allen, Jonathan E.
    Maslov, Sergei
    Holbeck, Susan L.
    Doroshow, James H.
    Evrard, Yvonne A.
    Stahlberg, Eric A.
    Stevens, Rick L.
    BMC BIOINFORMATICS, 2018, 19
  • [2] Single-Cell Techniques and Deep Learning in Predicting Drug Response
    Wu, Zhenyu
    Lawrence, Patrick J.
    Ma, Anjun
    Zhu, Jian
    Xu, Dong
    Ma, Qin
    TRENDS IN PHARMACOLOGICAL SCIENCES, 2020, 41 (12) : 1050 - 1065
  • [3] Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning
    Hassan, Mehdi
    Ali, Safdar
    Sanaullah, Muhammad
    Shahzad, Khuram
    Mushtaq, Sadaf
    Abbasi, Rashda
    Ali, Zulqurnain
    Alquhayz, Hani
    CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 70 (02): : 2743 - 2760
  • [4] Predicting Anticancer Drug Response With Deep Learning Constrained by Signaling Pathways
    Zhang, Heming
    Chen, Yixin
    Li, Fuhai
    FRONTIERS IN BIOINFORMATICS, 2021, 1
  • [5] Predicting drug response through tumor deconvolution by cancer cell lines
    Hsu, Yu-Ching
    Chiu, Yu-Chiao
    Lu, Tzu-Pin
    Hsiao, Tzu-Hung
    Chen, Yidong
    PATTERNS, 2024, 5 (04):
  • [6] MSDRP: a deep learning model based on multisource data for predicting drug response
    Zhao, Haochen
    Zhang, Xiaoyu
    Zhao, Qichang
    Li, Yaohang
    Wang, Jianxin
    BIOINFORMATICS, 2023, 39 (09)
  • [7] Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells
    Kuenzi, Brent M.
    Park, Jisoo
    Fong, Samson H.
    Sanchez, Kyle S.
    Lee, John
    Kreisberg, Jason F.
    Ma, Jianzhu
    Ideker, Trey
    CANCER CELL, 2020, 38 (05) : 672 - +
  • [8] Predicting breast cancer drug response using a multiple-layer cell line drug response network model
    Huang, Shujun
    Hu, Pingzhao
    Lakowski, Ted M.
    BMC CANCER, 2021, 21 (01)
  • [9] Predicting breast cancer drug response using a multiple-layer cell line drug response network model
    Shujun Huang
    Pingzhao Hu
    Ted M. Lakowski
    BMC Cancer, 21
  • [10] Predicting the mechanical response of oligocrystals with deep learning
    Frankel, A. L.
    Jones, R. E.
    Alleman, C.
    Templeton, J. A.
    COMPUTATIONAL MATERIALS SCIENCE, 2019, 169
12345