Advanced computing for systems biology

Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

A model for motion sharpening: contrast gain control precedes compressive nonlinearity

Blurred edges appear sharper in motion than when they are stationary. We have previously shown how such distortions in perceived edge blur may be explained by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. To test this model further, we measured the sharpening of drifting, periodic patterns over a large range of contrasts, blur widths, and speeds Human Vision. The results indicate that, while sharpening increased with speed, it was practically invariant with contrast. This contrast invariance cannot be explained by a fixed compressive nonlinearity since that predicts almost no sharpening at low contrasts.We show by computational modelling of spatiotemporal responses that, if a dynamic contrast gain control precedes the static nonlinear transducer, then motion sharpening, its speed dependence, and its invariance with contrast can be predicted with reasonable accuracy.

Models and empirical data for the production of referring expressions

Article Accepted Date: 29 May 2014 Acknowledgements The authors gratefully acknowledge the support of the Cognitive Science Society for the organisation of the Workshop on Production of Referring Expressions: Bridging the Gap between Cognitive and Computational Approaches to Reference, from which this special issue originated. Funding Emiel Krahmer and Albert Gatt thank The Netherlands Organisation for Scientific Research (NWO) for VICI grant Bridging the Gap between Computational Linguistics and Psycholinguistics: The Case of Referring Expressions (grant number 277-70-007).

A contribution towards the performance and structural understanding of copper and nickel salts as ammonia stores

The ongoing depletion of fossil fuels and the severe consequences of the greenhouse effect make the development of alternative energy systems crucially important. While hydrogen is, in principle, a promising alternative, releasing nothing but energy and pure water. Hydrogen storage is complicated and no completely viable technique has been proposed so far. This work is concerned with the study of one potential alternative to pure hydrogen: ammonia, and more specifically its storage in solids. Ammonia, NH3, can be regarded as a chemical hydrogen carrier with the advantages of strongly reduced flammability and explosiveness as compared to hydrogen. Furthermore, ammine metal salts presented here as promising ammonia stores easily store up to 50 wt.-% ammonia, giving them a volumetric energy density comparable to natural gas. The model system NiX2–NH3 ( X = Cl, Br, I) is studied thoroughly with respect to ammine salt formation, thermal decomposition, air stability and structural effects. The system CuX2–NH3 ( X = Cl, Br) has an adverse thermal decomposition behaviour, making it impractical for use as an ammonia store. This system is, however, most interesting from a structural point of view and some work concerning the study of the structural behaviour of this system is presented. Finally, close chemical relatives to the metal ammine halides, the metal ammine nitrates are studied. They exhibit interesting anion arrangements, which is an impressive showcase for the combination of diffraction and spectroscopic information. The characterisation techniques in this thesis range from powder diffraction over single crystal diffraction, spectroscopy, computational modelling, thermal analyses to gravimetric uptake experiments. Further highlights are the structure solutions and refinements from powder data of (NH4)2[NiCl4(H2O)(NH3)] and Ni(NH3)2(NO3)2, the combination of crystallographic and chemical information for the elucidation of the (NH4)2[NiCl4(H2O)(NH3)] formation reaction and the growth of single crystals under ammonia flow, a technique allowing the first documented successful growth and single crystal diffraction measurement for [Cu(NH3)6]Cl2.

Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Computational analysis of laminated glass panels under blast loads: A comparison of two dimensional and three dimensional modelling approaches

This paper illustrates the use of finite element (FE) technique to investigate the behaviour of laminated glass (LG) panels under blast loads. Two and three dimensional (2D and 3D) modelling approaches available in LS-DYNA FE code to model LG panels are presented. Results from the FE analysis for mid-span deflection and principal stresses compared well with those from large deflection plate theory. The FE models are further validated using the results from a free field blast test on a LG panel. It is evident that both 2D and 3D LG models predict the experimental results with reasonable accuracy. The 3D LG models give slightly more accurate results but require considerably more computational time compared to the 2D LG models.