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Dive into the research topics where James Hetherington is active.

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Featured researches published by James Hetherington.


IEEE Computer | 2004

Computational challenges of systems biology

Anthony Finkelstein; James Hetherington; L Li; O Margoninski; Peter Saffrey; Robert M. Seymour; Anne E. Warner

Progress in the study of biological systems such as the heart, brain, and liver will require computer scientists to work closely with life scientists and mathematicians. Computer science will play a key role in shaping the new discipline of systems biology and addressing the significant computational challenges it poses.


Physical Review E | 2014

Choice of boundary condition for lattice-Boltzmann simulation of moderate-Reynolds-number flow in complex domains

Rupert W. Nash; Hywel B. Carver; Miguel O. Bernabeu; James Hetherington; Derek Groen; Timm Krueger; Peter V. Coveney

Modeling blood flow in larger vessels using lattice-Boltzmann methods comes with a challenging set of constraints: a complex geometry with walls and inlets and outlets at arbitrary orientations with respect to the lattice, intermediate Reynolds (Re) number, and unsteady flow. Simple bounce-back is one of the most commonly used, simplest, and most computationally efficient boundary conditions, but many others have been proposed. We implement three other methods applicable to complex geometries [Guo, Zheng, and Shi, Phys. Fluids 14, 2007 (2002); Bouzidi, Firdaouss, and Lallemand, Phys. Fluids 13, 3452 (2001); Junk and Yang, Phys. Rev. E 72, 066701 (2005)] in our open-source application hemelb. We use these to simulate Poiseuille and Womersley flows in a cylindrical pipe with an arbitrary orientation at physiologically relevant Re number (1-300) and Womersley (4-12) numbers and steady flow in a curved pipe at relevant Dean number (100-200) and compare the accuracy to analytical solutions. We find that both the Bouzidi-Firdaouss-Lallemand (BFL) and Guo-Zheng-Shi (GZS) methods give second-order convergence in space while simple bounce-back degrades to first order. The BFL method appears to perform better than GZS in unsteady flows and is significantly less computationally expensive. The Junk-Yang method shows poor stability at larger Re number and so cannot be recommended here. The choice of collision operator (lattice Bhatnagar-Gross-Krook vs multiple relaxation time) and velocity set (D3Q15 vs D3Q19 vs D3Q27) does not significantly affect the accuracy in the problems studied.


Journal of Chemical Physics | 2013

Parallel kinetic Monte Carlo simulation framework incorporating accurate models of adsorbate lateral interactions

Jens H. Nielsen; Mayeul d’Avezac; James Hetherington; Michail Stamatakis

Ab initio kinetic Monte Carlo (KMC) simulations have been successfully applied for over two decades to elucidate the underlying physico-chemical phenomena on the surfaces of heterogeneous catalysts. These simulations necessitate detailed knowledge of the kinetics of elementary reactions constituting the reaction mechanism, and the energetics of the species participating in the chemistry. The information about the energetics is encoded in the formation energies of gas and surface-bound species, and the lateral interactions between adsorbates on the catalytic surface, which can be modeled at different levels of detail. The majority of previous works accounted for only pairwise-additive first nearest-neighbor interactions. More recently, cluster-expansion Hamiltonians incorporating long-range interactions and many-body terms have been used for detailed estimations of catalytic rate [C. Wu, D. J. Schmidt, C. Wolverton, and W. F. Schneider, J. Catal. 286, 88 (2012)]. In view of the increasing interest in accurate predictions of catalytic performance, there is a need for general-purpose KMC approaches incorporating detailed cluster expansion models for the adlayer energetics. We have addressed this need by building on the previously introduced graph-theoretical KMC framework, and we have developed Zacros, a FORTRAN2003 KMC package for simulating catalytic chemistries. To tackle the high computational cost in the presence of long-range interactions we introduce parallelization with OpenMP. We further benchmark our framework by simulating a KMC analogue of the NO oxidation system established by Schneider and co-workers [J. Catal. 286, 88 (2012)]. We show that taking into account only first nearest-neighbor interactions may lead to large errors in the prediction of the catalytic rate, whereas for accurate estimates thereof, one needs to include long-range terms in the cluster expansion.


Interface Focus | 2013

Flexible composition and execution of high performance, high fidelity multiscale biomedical simulations.

Derek Groen; Joris Borgdorff; Carles Bona-Casas; James Hetherington; Rupert W. Nash; Stefan J. Zasada; Ilya Saverchenko; Mariusz Mamonski; Krzysztof Kurowski; Miguel O. Bernabeu; Alfons G. Hoekstra; Peter V. Coveney

Multiscale simulations are essential in the biomedical domain to accurately model human physiology. We present a modular approach for designing, constructing and executing multiscale simulations on a wide range of resources, from laptops to petascale supercomputers, including combinations of these. Our work features two multiscale applications, in-stent restenosis and cerebrovascular bloodflow, which combine multiple existing single-scale applications to create a multiscale simulation. These applications can be efficiently coupled, deployed and executed on computers up to the largest (peta) scale, incurring a coupling overhead of 1–10% of the total execution time.


Journal of open research software | 2014

Summary of the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1)

Daniel S. Katz; Sou-Cheng T. Choi; Hilmar Lapp; Ketan Maheshwari; Frank Löffler; Matthew J. Turk; Marcus D. Hanwell; Nancy Wilkins-Diehr; James Hetherington; James Howison; Shel Swenson; Gabrielle Allen; Anne C. Elster; G. Bruce Berriman; Colin C. Venters

Challenges related to development, deployment, and maintenance of reusable software for science are becoming a growing concern. Many scientists’ research increasingly depends on the quality and availability of software upon which their works are built. To highlight some of these issues and share experiences, the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1) was held in November 2013 in conjunction with the SC13 Conference. The workshop featured keynote presentations and a large number (54) of solicited extended abstracts that were grouped into three themes and presented via panels. A set of collaborative notes of the presentations and discussion was taken during the workshop. Unique perspectives were captured about issues such as comprehensive documentation, development and deployment practices, software licenses and career paths for developers. Attribution systems that account for evidence of software contribution and impact were also discussed. These include mechanisms such as Digital Object Identifiers, publication of “software papers”, and the use of online systems, for example source code repositories like GitHub. This paper summarizes the issues and shared experiences that were discussed, including cross-cutting issues and use cases. It joins a nascent literature seeking to understand what drives software work in science, and how it is impacted by the reward systems of science. These incentives can determine the extent to which developers are motivated to build software for the long-term, for the use of others, and whether to work collaboratively or separately. It also explores community building, leadership, and dynamics in relation to successful scientific software.


Journal of Computational Science | 2013

Analysing and modelling the performance of the HemeLB lattice-Boltzmann simulation environment

Derek Groen; James Hetherington; Hywel B. Carver; Rupert W. Nash; Miguel O. Bernabeu; Peter V. Coveney

We investigate the performance of the HemeLB lattice-Boltzmann simulator for cerebrovascular blood flow, aimed at providing timely and clinically relevant assistance to neurosurgeons. HemeLB is optimised for sparse geometries, supports interactive use, and scales well to 32,768 cores for problems with ∼81 million lattice sites. We obtain a maximum performance of 29.5 billion site updates per second, with only an 11% slowdown for highly sparse problems (5% fluid fraction). We present steering and visualisation performance measurements and provide a model which allows users to predict the performance, thereby determining how to run simulations with maximum accuracy within time constraints.


Journal of the Royal Society Interface | 2014

Computer simulations reveal complex distribution of haemodynamic forces in a mouse retina model of angiogenesis

Miguel O. Bernabeu; Martin L. Jones; Jens H. Nielsen; Timm Krüger; Rupert W. Nash; Derek Groen; Sebastian Schmieschek; James Hetherington; Holger Gerhardt; Claudio A. Franco; Peter V. Coveney

There is currently limited understanding of the role played by haemodynamic forces on the processes governing vascular development. One of many obstacles to be overcome is being able to measure those forces, at the required resolution level, on vessels only a few micrometres thick. In this paper, we present an in silico method for the computation of the haemodynamic forces experienced by murine retinal vasculature (a widely used vascular development animal model) beyond what is measurable experimentally. Our results show that it is possible to reconstruct high-resolution three-dimensional geometrical models directly from samples of retinal vasculature and that the lattice-Boltzmann algorithm can be used to obtain accurate estimates of the haemodynamics in these domains. We generate flow models from samples obtained at postnatal days (P) 5 and 6. Our simulations show important differences between the flow patterns recovered in both cases, including observations of regression occurring in areas where wall shear stress (WSS) gradients exist. We propose two possible mechanisms to account for the observed increase in velocity and WSS between P5 and P6: (i) the measured reduction in typical vessel diameter between both time points and (ii) the reduction in network density triggered by the pruning process. The methodology developed herein is applicable to other biomedical domains where microvasculature can be imaged but experimental flow measurements are unavailable or difficult to obtain.


Computers & Chemical Engineering | 2007

Addressing the challenges of multiscale model management in systems biology

James Hetherington; I.D.L. Bogle; Peter Saffrey; O Margoninski; L Li; M. Varela Rey; Sachie Yamaji; S. Baigent; Jonathan Ashmore; K. Page; Robert M. Seymour; Anthony Finkelstein; Anne E. Warner

Mathematical and computational modelling are emerging as important techniques for studying the behaviour of complex biological systems. We argue that two advances are necessary to properly leverage these techniques: firstly, the ability to integrate models developed and executed on separate tools, without the need for substantial translation and secondly, a comprehensive system for storing and man-ageing not only the models themselves but also the parameters and tools used to execute those models and the results they produce. A framework for modelling with these features is described here. We have developed of a suite of XML-based services used for the storing and analysis of models, model parameters and results, and tools for model integration. We present these here, and evaluate their effectiveness using a worked example based on part of the hepatocyte glycogenolysis system.


Journal of the Royal Society Interface | 2012

A composite computational model of liver glucose homeostasis. I. Building the composite model

James Hetherington; T. Sumner; Robert M. Seymour; L Li; M. Varela Rey; Sachie Yamaji; Peter Saffrey; O Margoninski; I.D.L. Bogle; Anthony Finkelstein; Anne E. Warner

A computational model of the glucagon/insulin-driven liver glucohomeostasis function, focusing on the buffering of glucose into glycogen, has been developed. The model exemplifies an ‘engineering’ approach to modelling in systems biology, and was produced by linking together seven component models of separate aspects of the physiology. The component models use a variety of modelling paradigms and degrees of simplification. Model parameters were determined by an iterative hybrid of fitting to high-scale physiological data, and determination from small-scale in vitro experiments or molecular biological techniques. The component models were not originally designed for inclusion within such a composite model, but were integrated, with modification, using our published modelling software and computational frameworks. This approach facilitates the development of large and complex composite models, although, inevitably, some compromises must be made when composing the individual models. Composite models of this form have not previously been demonstrated.


Journal of open research software | 2016

Report on the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3).

Daniel S. Katz; Sou-Cheng T. Choi; Kyle E. Niemeyer; James Hetherington; Frank Löffler; Dan Gunter; Ray Idaszak; Steven R. Brandt; Mark A. Miller; Sandra Gessing; Nick Jones; Nic Weber; Suresh Marru; Gabrielle Allen; Birgit Penzenstadler; Colin C. Venters; Ethan Davis; Lorraine Hwang; Ilian Todorov; Abani K. Patra; Miguel de Val-Borro

This report records and discusses the Third Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE3). The report includes a description of the keynote presentation of the workshop, which served as an overview of sustainable scientific software. It also summarizes a set of lightning talks in which speakers highlighted to-the-point lessons and challenges pertaining to sustaining scientific software. The final and main contribution of the report is a summary of the discussions, future steps, and future organization for a set of self-organized working groups on topics including developing pathways to funding scientific software; constructing useful common metrics for crediting software stakeholders; identifying principles for sustainable software engineering design; reaching out to research software organizations around the world; and building communities for software sustainability. For each group, we include a point of contact and a landing page that can be used by those who want to join that group’s future activities. The main challenge left by the workshop is to see if the groups will execute these activities that they have scheduled, and how the WSSSPE community can encourage this to happen.

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Rupert W. Nash

University College London

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Derek Groen

University College London

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Anne E. Warner

University College London

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O Margoninski

University College London

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L Li

University College London

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Peter Saffrey

University College London

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