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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 |
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author | Dougherty, Edward R Boulesteix, Anne-Laure Dalton, Lori A Zhang, Michelle |
author_facet | Dougherty, Edward R Boulesteix, Anne-Laure Dalton, Lori A Zhang, Michelle |
author_sort | Dougherty, Edward R |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5843086 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-58430862018-03-12 Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy Dougherty, Edward R Boulesteix, Anne-Laure Dalton, Lori A Zhang, Michelle Cancer Inform Editorial: Special Collection: 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. 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. SAGE Publications 2018-03-05 /pmc/articles/PMC5843086/ /pubmed/29531471 http://dx.doi.org/10.1177/1176935118760944 Text en © The Author(s) 2018 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages(https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Editorial: Special Collection: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy Dougherty, Edward R Boulesteix, Anne-Laure Dalton, Lori A Zhang, Michelle Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
title | Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
title_full | Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
title_fullStr | Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
title_full_unstemmed | Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
title_short | Guest Editorial—Special Collection Topic: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
title_sort | guest editorial—special collection topic: statistical systems theory in cancer modeling, diagnosis, and therapy |
topic | Editorial: Special Collection: Statistical Systems Theory in Cancer Modeling, Diagnosis, and Therapy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5843086/ https://www.ncbi.nlm.nih.gov/pubmed/29531471 http://dx.doi.org/10.1177/1176935118760944 |
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