Striking a Balance Between Feasible and Realistic Biological Models

被引:2
|
作者
Califano, Andrea [1 ,2 ,3 ,4 ,5 ,6 ]
机构
[1] Columbia Univ, Columbia Initiat Syst Biol, New York, NY 10032 USA
[2] Columbia Univ, Ctr Computat Biol & Bioinformat, New York, NY 10032 USA
[3] Columbia Univ, Dept Biomed Informat, New York, NY 10032 USA
[4] Columbia Univ, Dept Biochem & Mol Biophys, New York, NY 10032 USA
[5] Columbia Univ, Inst Canc Genet, New York, NY 10032 USA
[6] Columbia Univ, Herbert Irving Comprehens Canc Ctr, New York, NY 10032 USA
关键词
TUMOR-REGRESSION; MYC INACTIVATION; CANCER; ONCOGENE; CELLS; PROLIFERATION; ADDICTION; THERAPY; GROWTH; BRAIN;
D O I
10.1126/scitranslmed.3003079
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
The fusion of empirical science with large-scale computing platforms has allowed rapid advances in our ability to model physiological and pathophysiological processes in silico. In this week's issue of Science Translational Medicine, Tran et al. present a simple framework for the quantitative modeling of oncogene addiction that provides mechanistic insights into tumor biology.
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页数:3
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