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Systems Biology, IET

Issue 6 • Date November 2008

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Displaying Results 1 - 5 of 5
  • Editorial - Selected papers from the 'Omics: Assembling Systems Biology' Workshop

    Page(s): 383 - 384
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (131 KB)  

    System-oriented biological research (Systems Biology) is a vibrant field which aims to establish the higher-order principles behind complex multi-cellular processes. This classic theme of the Life Sciences was recently reinforced with a new armamentarium of high-throughput molecular tools. These omics approaches ('omes', greek for 'complete') allow us to now study biological behaviour in unprecedented width and detail. Consequently, Systems Biology is seen to bear the potential for major discoveries in the Life Sciences. View full abstract»

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  • Computational inference of replication and transcription activator regulator activity in herpesvirus from gene expression data

    Page(s): 385 - 396
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (489 KB)  

    One of the main aims of system biology is to understand the structure and dynamics of genomic systems. A computational approach, facilitated by new technologies for high-throughput quantitative experimental data, is put forward to investigate the regulatory system of dynamic interaction among genes in Kaposi's sarcoma-associated herpesvirus network after induction of lytic replication. A reconstruction of transcription factor activity and gene-regulatory kinetics using data from a time-course microarray experiment is proposed. The computational approach uses nonlinear differential equations. In particular, the quantitative Michaelis-Menten model of gene- regulatory kinetics is extended to allow for post-transcriptional modifications and synergic interactions between target genes and the Rta transcription factor. The kinetic method is developed within a Bayesian inferential framework using Markov chain Monte Carlo. The profile of the Rta transcriptional regulator, other post- transcriptional regulatory genes and gene-specific kinetic parameters are inferred from the gene expression data of the target genes. The method described here provides an example of a principled approach to handle a wide range of transcriptional network architectures and regulatory activation mechanisms to reconstruct the activity of several transcription factors and activation kinetic parameters in a single regulatory network. View full abstract»

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  • Control, responses and modularity of cellular regulatory networks: a control analysis perspective

    Page(s): 397 - 410
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (295 KB)  

    Cells adapt to changes in environmental conditions through the concerted action of signalling, gene expression and metabolic subsystems. The authors will discuss a theoretical framework addressing such integrated systems. This dasiahierarchical analysisdasia was first developed as an extension to a metabolic control analysis. It builds on the phenomenon that often the communication between signalling, gene expression and metabolic subsystems is almost exclusively via regulatory interactions and not via mass flow interactions. This allows for the treatment of the said subsystems as dasialevelsdasia in a hierarchical view of the organisation of the molecular reaction network of cells. Such a hierarchical approach has as a major advantage that levels can be analysed conceptually in isolation of each other (from a local intra-level perspective) and at a later stage integrated via their interactions (from a global inter-level perspective). Hereby, it allows for a modular approach with variable scope. A number of different approaches have been developed for the analysis of hierarchical systems, for example hierarchical control analysis and modular response analysis. The authors, here, review these methods and illustrate the strength of these types of analyses using a core model of a system with gene expression, metabolic and signal transduction levels. View full abstract»

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  • Computational modelling identifies the impact of subtle anatomical variations between amphibian and mammalian skeletal muscle on spatiotemporal calcium dynamics

    Page(s): 411 - 422
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (409 KB)  

    The physical sites of calcium entry and exit in the skeletal muscle cell are distinct and highly organised in space. It was investigated whether the highly structured spatial organisation of sites of Ca2+ release, uptake and action in skeletal muscle cells substantially impacts the dynamics of cytosolic Ca2+ handling and thereby the physiology of the cell. Hereto, the spatiotemporal dynamics of the free calcium distribution in a fast-twitch (FT) muscle sarcomere was studied using a reaction-diffusion computational model for two genotypes with known anatomical differences. A computational model of a murine FT muscle sarcomere is developed, de novo including a closed calcium mass balance to simulate spatiotemporal high stimulation frequency calcium dynamics at 35degC. Literature data on high-frequency calcium dye measurements were used as a first step towards model validation. The murine and amphibian sarcomere models were phenotypically distinct to capture known differences in positions of troponin C, actindegmyosin overlap and calcium release within the sarcomere between frog and mouse. The models predicted large calcium gradients throughout the myoplasm as well as differences in calcium concentrations near the mitochondria of frog and mouse. Furthermore, the predicted Ca2+ concentration was high at positions where Ca2+ has a regulatory function, close to the mitochondria and troponin C. View full abstract»

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  • Genetical systems biology in livestock: application to gonadotrophin releasing hormone and reproduction

    Page(s): 423 - 441
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (1529 KB)  

    Genetical systems biology or systems genetics treats the genome as the central reference point for all omics variations and is an emerging new branch of systems biology. Quantitative genetic principles were developed for high-throughput genomic, transcriptomic and metabolomic data observed in large populations. New statistical genetic models were developed for expression quantitative trait loci (eQTL), namely, marker regression eQTL mapping and marker-expression co-factor mapping. Evaluations of power to detect eQTL showed that sample size requirements are higher for detecting trans-acting genes than cis-acting genes. Power is higher for eQTL with high heritability than for eQTL with low heritability. These results will be valuable for systems genetic investigations. Gonadotrophin releasing hormone (GnRH) and its receptor gene (GnRH-R) are crucial for mammalian reproduction. Whole genome scan of eQTLs for GnRH-R gene expression in mouse showed three possible trans-eQTL regions on chr 13 and 19, harbouring regulatory genes. Applications of genetical genomics in systems biology were identified as: (1) detection and validation of causal gene for complex traits; (2) development of genetic interaction networks; (3) prediction of transcription factor binding sites and (4) in data-driven systems biology. These applications were illustrated using data on eQTL, protein network and signalling pathways for GnRH. Gpr54 (G protein-coupled receptor kinase 54), Prl (prolactin), Ins1 (insulin) and Fos (viral oncogenes) were found to be major regulators of GnRH and GnRH-R; thus validating their important role in reproduction, mammary gland development and sexual (im)maturity. These results will be useful for further study of mammalian reproductive biology. View full abstract»

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Aims & Scope

IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches.

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