Publications

Publications from our Researchers

Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.  

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  • Conference paper
    Tauheed F, Nobari S, Biveinis L, Heinis T, Ailamaki Aet al., 2013,

    Computational Neuroscience Breakthroughs through Innovative Data Management

    , Pages: 14-27
  • Journal article
    Dalby AR, Emam I, Franke R, 2012,

    Analysis of Gene Expression Data from Non-Small Cell Lung Carcinoma Cell Lines Reveals Distinct Sub-Classes from Those Identified at the Phenotype Level

    , PLOS ONE, Vol: 7, ISSN: 1932-6203
  • Journal article
    Yang X, Han R, Guo Y, Bradley J, Cox B, Dickinson R, Kitney Ret al., 2012,

    Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA

    , Bmc Bioinformatics, Vol: 13, ISSN: 1471-2105
  • Conference paper
    Holehouse A, Yang X, Adcock I, Guo Yet al., 2012,

    Developing a novel integrated model of p38 MAPK and glucocorticoid signalling pathways

    , Pages: 69-76
  • Journal article
    Parkinson H, Sarkans U, Kolesnikov N, Abeygunawardena N, Burdett T, Dylag M, Emam I, Farne A, Hastings E, Holloway E, Kurbatova N, Lukk M, Malone J, Mani R, Pilicheva E, Rustici G, Sharma A, Williams E, Adamusiak T, Brandizi M, Sklyar N, Brazma Aet al., 2011,

    ArrayExpress update-an archive of microarray and high-throughput sequencing-based functional genomics experiments

    , NUCLEIC ACIDS RESEARCH, Vol: 39, Pages: D1002-D1004, ISSN: 0305-1048
  • Journal article
    Huntley DM, Pandis I, Butcher SA, Ackers JPet al., 2010,

    Bioinformatic analysis of <i>Entamoeba histolytica</i> SINE1 elements

    , BMC GENOMICS, Vol: 11, ISSN: 1471-2164
  • Journal article
    Kapushesky M, Emam I, Holloway E, Kurnosov P, Zorin A, Malone J, Rustici G, Williams E, Parkinson H, Brazma Aet al., 2010,

    Gene Expression Atlas at the European Bioinformatics Institute

    , NUCLEIC ACIDS RESEARCH, Vol: 38, Pages: D690-D698, ISSN: 0305-1048
  • Journal article
    Curcin V, Ghanem M, Guo Y, 2010,

    Polymorphic type framework for scientific workflows with relational data model

    , International Journal of Business Process Integration and Management, Vol: 5, Pages: 45+-45+, ISSN: 1741-8763
  • Journal article
    Curcin V, Ghanem M, Guo Y, 2010,

    The design and implementation of a workflow analysis tool

    , Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol: 368, Pages: 4193-4208
  • Journal article
    Wang FZ, Helian N, Wu S, Guo Y, Deng DY, Meng L, Zhang W, Crowcroft J, Bacon J, Parker MAet al., 2009,

    Eight Times Acceleration of Geospatial Data Archiving and Distribution on the Grids (vol 47, pg 1444, 2009)

    , IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, Vol: 47, Pages: 2988-2988, ISSN: 0196-2892
  • Journal article
    Parkinson H, Kapushesky M, Kolesnikov N, Rustici G, Shojatalab M, Abeygunawardena N, Berube H, Dylag M, Emam I, Farne A, Holloway E, Lukk M, Malone J, Mani R, Pilicheva E, Rayner TF, Rezwan F, Sharma A, Williams E, Bradley XZ, Adamusiak T, Brandizi M, Burdett T, Coulson R, Krestyaninova M, Kurnosov P, Maguire E, Neogi SG, Rocca-Serra P, Sansone S-A, Sklyar N, Zhao M, Sarkans U, Brazma Aet al., 2009,

    ArrayExpress update-from an archive of functional genomics experiments to the atlas of gene expression

    , NUCLEIC ACIDS RESEARCH, Vol: 37, Pages: D868-D872, ISSN: 0305-1048
  • Journal article
    Curcin V, Ghanem M, Guo Y, 2009,

    Analysing scientific workflows with Computational Tree Logic. Journal of Cluster Computing

    , Journal of Cluster Computing: Special Issue of Recent Advances in e-Science, ISSN: 1386-7857

    Motivated by the widespread use of workflow systems in e-Science applications, this article introduces a formal analysis framework for the verification and profiling of the control flow aspects of scientific workflows. The framework relies on process algebras that characterise each workflow component with a process behaviour, which is then used to build a CTL state model that can be reasoned about. We demonstrate the benefits of the approach by modelling the control flow behaviour of the Discovery Net system, one of the earliest workflow-based e-Science systems, and present how some key properties of workflows and individual service utilisation can be queried at design time. Our approach is generic and can be applied easily to modelling workflows developed in any other system. It also provides a formal basis for the comparison of control aspects of e-Science workflow systems and a design method for future systems.
  • Conference paper
    Curcin V, Ghanem M, Guo Y, Darlington Jet al., 2008,

    Mining adverse drug reactions with e-science workflows.

    , Proceedings of the 4th Cairo International Biomedical Engineering Conference, 2008. CIBEC 2008
  • Book chapter
    Ghanem M, Curcin V, Wendel P, Guo Yet al., 2008,

    Building and using analytical workflows in Discovery Net

    , Data Mining Techniques in Grid Environments. Dubitzky, Werner (Ed)., Publisher: Wiley-Blackwell, Pages: 119-140, ISBN: 9780470512586

    The Discovery Net platform is built around a workflow model for integrating distributed data sources and analytical tools. The platform was originally designed to support the design and execution of distributed data mining tasks within a grid-based environment. However, over the years it has evolved into a generic data analysis platform with applications in such diverse areas as bioinformatics, cheminformatics, text mining and business intelligence. In this work we present our experience in designing the platform and map out the evolution paths for a workflow language, and its architecture, that need to address the requirements of different scientific domains.
  • Journal article
    Ma Y, Richards M, Ghanem M, Guo Y, Hassard Jet al., 2008,

    Air pollution monitoring and mining based on sensor grid in London

    , Sensors, Vol: 8, Pages: 3601-3623, ISSN: 1424-8220

    In this paper, we present a distributed infrastructure based on wireless sensors network and Grid computing technology for air pollution monitoring and mining, which aims to develop low-cost and ubiquitous sensor networks to collect real-time, large scale and comprehensive environmental data from road traffic emissions for air pollution monitoring in urban environment. The main informatics challenges in respect to constructing the high-throughput sensor Grid are discussed in this paper. We present a twolayer network framework, a P2P e-Science Grid architecture, and the distributed data mining algorithm as the solutions to address the challenges. We simulated the system in TinyOS to examine the operation of each sensor as well as the networking performance. We also present the distributed data mining result to examine the effectiveness of the algorithm.

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