Vera, Julio, Wolkenhauer, Olaf, and Schmitz, Ulf (2014) Cancer Systems Biology: Current Achievements in – Omics Data Analysis, Network Reconstruction and Mathematical Modelling. In: UNSPECIFIED, (ed.) Encyclopedia of Life Sciences. John Wiley & Sons, Chichester, UK, pp. 1-12.

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Abstract

Systems biology is a multidisciplinary methodology in which quantitative biological experimental data are dissected using mathematical modelling and other computational and network biology tools, aiming at understanding the structure, function and dynamical regulation of biochemical networks. Systems biology will play a major role in the future molecular and clinical oncology because (a) it can be used for the analysis of cancer-relevant high-throughput data, (b) it provides tools for the reconstruction of the large multilevel regulatory networks that govern critical cancer phenotypes and (c) it is necessary when investigating cancer-relevant networks holding multiple overlapping nonlinear regulatory motifs like feedback and feedforward loops. Here, the value of the systems biology approach in handling cancer genomics and transcriptomics data, the reconstruction of cancer networks and the use of mathematical modelling in the elucidation of cancer networks as well as in the design of anticancer therapies are discusses. Some recent case studies as proof of principle are highlighted.

Item ID:	69000
Item Type:	Book Chapter (Reference)
ISBN:	9780470015902
Keywords:	anticancer therapies, biochemical regulatory networks, feedback and feedforward loops, drug target detection, multi-scale cancer modelling, miRNA regulation, cancer genomics, cancer transcriptomics, patient stratification
Copyright Information:	Copyright © 2014 John Wiley & Sons, Ltd. All rights reserved.
Date Deposited:	31 Jul 2024 01:55
FoR Codes:	31 BIOLOGICAL SCIENCES > 3101 Biochemistry and cell biology > 310114 Systems biology @ 50% 31 BIOLOGICAL SCIENCES > 3102 Bioinformatics and computational biology > 310201 Bioinformatic methods development @ 50%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280102 Expanding knowledge in the biological sciences @ 100%
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