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Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy
Cancer is a systems disease involving mutations and altered regulation. This supplement treats cancer research as it pertains to 3 systems issues of an inherently statistical nature: regulatory modeling and information processing, diagnostic classification, and therapeutic intervention and control....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5843086/ https://www.ncbi.nlm.nih.gov/pubmed/29531471 http://dx.doi.org/10.1177/1176935118760944 |
Sumario: | Cancer is a systems disease involving mutations and altered regulation. This supplement treats cancer research as it pertains to 3 systems issues of an inherently statistical nature: regulatory modeling and information processing, diagnostic classification, and therapeutic intervention and control. Topics of interest include (but are not limited to) multiscale modeling, gene/protein transcriptional regulation, dynamical systems, pharmacokinetic/pharmacodynamic modeling, compensatory regulation, feedback, apoptotic and proliferative control, copy number-expression interaction, integration of different feature types, error estimation, and reproducibility. We are especially interested in how the above issues relate to the extremely high-dimensional data sets and small- to moderate-sized data sets typically involved in cancer research, for instance, their effect on statistical power, inference accuracy, and multiple comparisons. |
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