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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    Rustici G, Kolesnikov N, Brandizi M, Burdett T, Dylag M, Emam I, Farne A, Hastings E, Ison J, Keays M, Kurbatova N, Malone J, Mani R, Mupo A, Pereira RP, Pilicheva E, Rung J, Sharma A, Tang YA, Ternent T, Tikhonov A, Welter D, Williams E, Brazma A, Parkinson H, Sarkans Uet al., 2013,

    ArrayExpress update-trends in database growth and links to data analysis tools

    , NUCLEIC ACIDS RESEARCH, Vol: 41, Pages: D987-D990, ISSN: 0305-1048
    Stougiannis A, Pavlovic M, Tauheed F, Heinis T, Ailamaki Aet al., 2013,

    Data-driven neuroscience: enabling breakthroughs via innovative data management.

    , Publisher: ACM, Pages: 953-956
    Stougiannis A, Tauheed F, Heinis T, Ailamaki Aet al., 2013,

    Accelerating spatial range queries.

    , Publisher: ACM, Pages: 713-716
    Strege C, Bertone G, Feroz F, Fornasa M, Ruiz de Austri R, Trotta Ret al., 2013,

    Global fits of the cMSSM and NUHM including the LHC Higgs discovery and new XENON100 constraints

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

    Computational Neuroscience Breakthroughs through Innovative Data Management.

    , Publisher: Springer, Pages: 14-27
    Wu C, Guo Y, 2013,

    Enhanced User Data Privacy with Pay-by-Data Model

    , IEEE International Conference on Big Data (Big Data), Publisher: IEEE
    Birch D, 2012,

    Computational Investigations in Masterplan Design

    , Arup Doctoral College Conference
    Chao W, Guo Y, Zhou B, 2012,

    Social networking federation: A position paper

    , COMPUTERS & ELECTRICAL ENGINEERING, Vol: 38, Pages: 306-329, ISSN: 0045-7906
    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
    Dustdar S, Guo Y, Han R, Satzger B, Hong-Linh Tet al., 2012,

    Programming Directives for Elastic Computing

    , IEEE INTERNET COMPUTING, Vol: 16, Pages: 72-77, ISSN: 1089-7801
    Guo Y, Ghanem M, Han R, 2012,

    Does the Cloud Need New Algorithms? An Introduction to Elastic Algorithms

    , 4th IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Publisher: IEEE, ISSN: 2330-2194
    Guo Y, Yang X, 2012,

    System Biology Approach to Study Cancer Related Pathway

    , Systems Biology in Cancer Research and Drug Discovery
    Han R, Guo L, Ghanem MM, Guo Yet al., 2012,

    Lightweight Resource Scaling for Cloud Applications

    , Washington, DC, USA, Publisher: IEEE Computer Society, Pages: 644-651
    He S, Guo L, Ghanem M, Guo Yet al., 2012,

    Improving resource utilisation in the cloud environment using multivariate probabilistic models

    , Pages: 574-581

    Resource provisioning based on virtual machine (VM) has been widely accepted and adopted in cloud computing environments. A key problem resulting from using static scheduling approaches for allocating VMs on different physical machines (PMs) is that resources tend to be not fully utilised. Although some existing cloud reconfiguration algorithms have been developed to address the problem, they normally result in high migration costs and low resource utilisation due to ignoring the multi-dimensional characteristics of VMs and PMs. In this paper we present and evaluate a new algorithm for improving resource utilisation for cloud providers. By using a multivariate probabilistic model, our algorithm selects suitable PMs for VM re-allocation which are then used to generate a reconfiguration plan. We also describe two heuristics metrics which can be used in the algorithm to capture the multi-dimensional characteristics of VMs and PMs. By combining these two heuristics metrics in our experiments, we observed that our approach improves the resource utilisation level by around 8% for cloud providers, such as IC Cloud, which accept user-defined VM configurations and 14% for providers, such as Amazon EC2, which only provide limited types of VM configurations. © 2012 IEEE.

    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

    Glucocorticoid (GC) resistance is a key mechanism by which traditional asthma treatments become ineffective for patients, yet the molecular characteristics of the associated regulatory changes are largely unknown. Significant evidence suggests that crosstalk between p38 Mitogen Activated Protein Kinase (MAPK) and GC signalling pathways may contribute to this resistance. Based on a number of studies, a simplified GC signalling pathway model was developed and integrated with a pre-existing model of the p38 MAPK pathway. It is predicted that with experimental data, the validity and use of this model can be confirmed, corrections and updates can be made where necessary, and that through the two pathways' interface points the existence and scale of crosstalk can be examined. © 2012 IEEE.

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