Computational Approaches in Theranostics: Mining and Predicting Cancer Data
Abstract
:1. Introduction
1.1. Connecting Computational Approaches and Theranostics
1.2. Relating In Silico and In Vivo Models
2. Different Models and Different Scales
3. Optimizing Diagnostic and Therapeutic Agents
4. Mapping Multidimensional Cancer Data
5. Concluding Remarks
Author Contributions
Funding
Conflicts of Interest
References
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Cova, T.F.G.G.; Bento, D.J.; Nunes, S.C.C. Computational Approaches in Theranostics: Mining and Predicting Cancer Data. Pharmaceutics 2019, 11, 119. https://doi.org/10.3390/pharmaceutics11030119
Cova TFGG, Bento DJ, Nunes SCC. Computational Approaches in Theranostics: Mining and Predicting Cancer Data. Pharmaceutics. 2019; 11(3):119. https://doi.org/10.3390/pharmaceutics11030119
Chicago/Turabian StyleCova, Tânia F. G. G., Daniel J. Bento, and Sandra C. C. Nunes. 2019. "Computational Approaches in Theranostics: Mining and Predicting Cancer Data" Pharmaceutics 11, no. 3: 119. https://doi.org/10.3390/pharmaceutics11030119
APA StyleCova, T. F. G. G., Bento, D. J., & Nunes, S. C. C. (2019). Computational Approaches in Theranostics: Mining and Predicting Cancer Data. Pharmaceutics, 11(3), 119. https://doi.org/10.3390/pharmaceutics11030119