Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy. (1st March 2018)

• Record Type: Journal Article
• Authors: Dougherty, Edward R; Boulesteix, Anne-Laure; Dalton, Lori A; Zhang, Michelle
• Is Part Of: Cancer informatics. Volume 17(2018)
• Publication Date: 2018-03-01
• Subjects: Bioinformatics -- Periodicals; Biology -- Data processing -- Periodicals; Cancer -- Periodicals; Cancer -- Research -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1177/1176935118760944
• Languages: English
• ISSNs: 1176-9351

Abstract

Aims and Scope: 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.