Research

  • Urban Interaction @ Glasgow (0)

    There has been a long history of research in “urban interaction” within the HCI and IR groups in the School of Computing science. Urban Interaction collects research articles over the last decade which deal with interactive systems in urban environments, including issues in running city-scale trials, multimodal pedestrian navigation, interactive technology in public spaces, and the use of social media in urban environments.

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    There has been a long history of research in “urban interaction” within the HCI and IR groups in the School of Computing science. Urban Interaction collects research articles over the last decade which deal with interactive systems in urban environments, including issues in running city-scale trials, multimodal pedestrian navigation, interactive technology in public spaces, and ...
  • Paper in Ecological Modelling (0)

    A group paper entitled “Discrete and continuous time simulations of spatial ecological processes predict different final population sizes and interspecific competition outcomes“, authored by Rebecca Mancy (IDI), Patrick Prosser (FATA, University of Glasgow) and Simon Rogers (IDI) is now in press with Ecological Modelling.

    The paper describes a set of computational experiments comparing ecological outcomes between a spatial version of the continuous time Gillespie algorithm and four discrete time cellular automaton algorithms. The simulations show that the decision about whether to model in discrete or continuous time matters for both dynamics and steady state outcomes. When simulating competition between two species, decisions about how to model time can even lead to differences in which species dominates. The work thus highlights the importance of modelling time in a way that reflects the dynamics of the system that is being modelled.

    The paper is available from Glasgow University’s Enlighten database or from Science Direct and the simulation code from the project’s GitHub page.

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    A group paper entitled “Discrete and continuous time simulations of spatial ecological processes predict different final population sizes and interspecific competition outcomes“, authored by Rebecca Mancy (IDI), Patrick Prosser (FATA, University of Glasgow) and Simon Rogers (IDI) is now in press with Ecological Modelling. The paper describes a set of computational experiments comparing ecological outcomes between a ...
  • Research: Metabolomics (0)

    The group performs research in the exciting field of systems biology. By applying modern Bayesian inference techniques, we hope to improve software tools that life scientists use to analyse data in metabolomics — the study of small molecules produced by fundamental chemical processes in every living being. Led by Dr. Simon Rogers, researchers from the IDI group work on the two biggest bottlenecks of metabolomics data analysis today: performing accurate identification of metabolites, and assigning biological significance to the result.

    metabolomics
    The figure above shows various metabolites to identify (top), and the mass spectra from experimental data (bottom). Accurately identifying metabolites from experimental data remains a challenging problem that has not been fully addressed. Improvements in metabolomics data analysis would enhance our understanding of other aspects of systems biology, such as functional genomicsnutrition researches and disease biomarkers detections.

    For more information, please contact the following researchers who are working on this subject:

    Related publications:
    1. Mixture Model Clustering for Peak Filtering in Metabolomics. Simon Rogers, Rónán Daly and Rainer Breitling. Proceedings of the 9th International Workshop on Computational Systems Biology, WCSB 2012 to appear.
    2. Probabilistic assignment of formulas to mass peaks in metabolomics experiments S. Rogers, R.E. Scheltema, M. Girolami, R. Breitling Bioinformatics 25(4) 2009, 512–518[Available online] [journal website].

    * Image by Markus Heinonen.

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    The group performs research in the exciting field of systems biology. By applying modern Bayesian inference techniques, we hope to improve software tools that life scientists use to analyse data in metabolomics — the study of small molecules produced by fundamental chemical processes in every living being. Led by Dr. Simon Rogers, researchers from the IDI group work ...
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