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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  • Journal article
    Strege C, Bertone G, Besjes GJ, Caron S, Ruiz de Austri R, Strubig A, Trotta Ret al., 2014,

    Profile likelihood maps of a 15-dimensional MSSM

    , Journal of High Energy Physics, Vol: 2014, ISSN: 1126-6708

    We present statistically convergent profile likelihood maps obtained via globalfits of a phenomenological Minimal Supersymmetric Standard Model with 15 free parameters(the MSSM-15), based on over 250M points. We derive constraints on the modelparameters from direct detection limits on dark matter, the Planck relic density measurementand data from accelerator searches. We provide a detailed analysis of the richphenomenology of this model, and determine the SUSY mass spectrum and dark matterproperties that are preferred by current experimental constraints. We evaluate the impactof the measurement of the anomalous magnetic moment of the muon (g −2) on our results,and provide an analysis of scenarios in which the lightest neutralino is a subdominant componentof the dark matter. The MSSM-15 parameters are relatively weakly constrained bycurrent data sets, with the exception of the parameters related to dark matter phenomenology(M1, M2, µ), which are restricted to the sub-TeV regime, mainly due to the relic densityconstraint. The mass of the lightest neutralino is found to be < 1.5 TeV at 99% C.L., butcan extend up to 3 TeV when excluding the g − 2 constraint from the analysis. Low-massbino-like neutralinos are strongly favoured, with spin-independent scattering cross-sectionsextending to very small values, ∼ 10−20 pb. ATLAS SUSY null searches strongly impacton this mass range, and thus rule out a region of parameter space that is outside the reachof any current or future direct detection experiment. The best-fit point obtained after inclusionof all data corresponds to a squark mass of 2.3 TeV, a gluino mass of 2.1 TeV and a130 GeV neutralino with a spin-independent cross-section of 2.4×10−10 pb, which is withinthe reach of future multi-ton scale direct detection experiments and of the upcoming LHCrun at increased centre-of-mass energy.

  • Journal article
    Martin J, Ringeval C, Trotta R, Vennin Vet al., 2014,

    Compatibility of Planck and BICEP2 results in light of inflation

    , PHYSICAL REVIEW D, Vol: 90, ISSN: 1550-7998
  • Journal article
    Nie L, Yang X, Adcock I, Xu Z, Guo Yet al., 2014,

    Inferring cell-scale signalling networks via compressive sensing

    , PLOS One, Vol: 9, ISSN: 1932-6203
  • Journal article
    Martin J, Ringeval C, Trotta R, Vennin Vet al., 2014,

    The best inflationary models after Planck

    , Journal of Cosmology and Astroparticle Physics, Vol: 2014, ISSN: 1475-7516

    We compute the Bayesian evidence and complexity of 193 slow-roll single-field models of inflation using the Planck 2013 Cosmic Microwave Background data, with the aim of establishing which models are favoured from a Bayesian perspective. Our calculations employ a new numerical pipeline interfacing an inflationary effective likelihood with the slow-roll library ASPIC and the nested sampling algorithm MultiNest. The models considered represent a complete and systematic scan of the entire landscape of inflationary scenarios proposed so far. Our analysis singles out the most probable models (from an Occam's razor point of view) that are compatible with Planck data, while ruling out with very strong evidence 34% of the models considered. We identify 26% of the models that are favoured by the Bayesian evidence, corresponding to 15 different potential shapes. If the Bayesian complexity is included in the analysis, only 9% of the models are preferred, corresponding to only 9 different potential shapes. These shapes are all of the plateau type.

  • Journal article
    Heinis T, 2014,

    Data analysis: Approximation aids handling of big data

    , Nature, Vol: 515, Pages: 198-198
  • Conference paper
    Wang S, Pandis I, Emam I, Johnson D, Guitton F, Oehmichen A, Guo Yet al., 2014,

    DSIMBench: A benchmark for Microarray Data using R

    , the 40th International Conference on Very Large Databases (VLDB 2014)
  • Journal article
    Wang S, Pandis I, Wu C, He S, Johnson D, Emam I, Guitton F, Guo Yet al., 2014,

    High Dimensional Biological Data Retrieval Optimization with NoSQL Technology

    , BMC Genomics, ISSN: 1471-2164
  • Journal article
    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


    We present global fits of the constrained Minimal Supersymmetric Standard Model (cMSSM) and the Non-Universal Higgs Model (NUHM), including the most recent CMS constraint on the Higgs boson mass, 5.8 fb−1 integrated luminosity null Supersymmetry searches by ATLAS, the new LHCb measurement of BR(bar Bs → μ+μ−) and the 7-year WMAP dark matter relic abundance determination. We include the latest dark matter constraints from the XENON100 experiment, marginalising over astrophysical and particle physics uncertainties. We present Bayesian posterior and profile likelihood maps of the highest resolution available today, obtained from up to 350M points. We find that the new constraint on the Higgs boson mass has a dramatic impact, ruling out large regions of previously favoured cMSSM and NUHM parameter space. In the cMSSM, light sparticles and predominantly gaugino-like dark matter with a mass of a few hundred GeV are favoured. The NUHM exhibits a strong preference for heavier sparticle masses and a Higgsino-like neutralino with a mass of 1 TeV. The future ton-scale XENON1T direct detection experiment will probe large portions of the currently favoured cMSSM and NUHM parameter space. The LHC operating at 14 TeV collision energy will explore the favoured regions in the cMSSM, while most of the regions favoured in the NUHM will remain inaccessible. Our best-fit points achieve a satisfactory quality-of-fit, with p-values ranging from 0.21 to 0.35, so that none of the two models studied can be presently excluded at any meaningful significance level.

  • Journal article
    Gow AM, Chung KF, Gibeon D, Guo Y, Batuwita K, Osmond M, Heaney L, Brightling C, Niven R, Mansur A, Chaudhuri R, Bucknall C, Rowe A, Bhavsar Pet al., 2013,

    Obesity associated severe asthma represents a distinct clinical phenotype – Analysis of the British Thoracic Society Difficult Asthma Registry patient cohort according to body mass index

    , CHEST Journal
  • Journal article
    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
  • Journal article
    Birch D, Kelly P, Field A, Simondetti Aet al., 2013,

    Computationally Unifying Urban Masterplanning

    , CF 2013 Proceedings of the ACM International Conference on Computing Frontiers, Pages: 1-10
  • Conference paper
    Birch D, Liang H, Ko J, Kelly P, Field A, Mullineux G, Simondetti Aet al., 2013,

    Multidisciplinary Engineering Models: Methodology and Case Study in Spreadsheet Analytics

    , European Spreadsheet Risks Interest Group 14th Annual Conference (EuSpRIG 2013), Publisher: EuSpRIG, Pages: 1-12
  • Conference paper
    Pavlovic M, Tauheed F, Heinis T, Ailamaki Aet al., 2013,

    GIPSY: joining spatial datasets with contrasting density

    , Pages: 11:1-11:12
  • Conference paper
    Stougiannis A, Pavlovic M, Tauheed F, Heinis T, Ailamaki Aet al., 2013,

    Data-driven neuroscience: enabling breakthroughs via innovative data management

    , Pages: 953-956
  • Conference paper
    Nobari S, Tauheed F, Heinis T, Karras P, Bressan S, Ailamaki Aet al., 2013,

    TOUCH: in-memory spatial join by hierarchical data-oriented partitioning

    , Pages: 701-712

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