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Dougherty, Edward R.; Boulesteix, Anne-Laure; Dalton, Lori A.; Zhang, Michelle (2018): Guest Editorial-Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy. In: Cancer informatics, Vol. 17
Full text not available from 'Open Access LMU'.

Abstract

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.