Most of the members of this group are from the Statistics Section and Biomaths research group of the Department of Mathematics. Below you can find a list of research areas that members of this group are currently working on and/or would like to work on by applying their developed mathematical and statistical methods.

Research areas

Research areas


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  • Journal article
    Bhatnagar N, Perkins K, Filippi S, Richmond H, Bonnici J, Alford K, Hall G, Juban G, McGowan S, Roy A, Elliott N, Stumpf M, Norton A, Vyas P, Roberts Iet al., 2014,

    Clinical and Hematologic Impact of Fetal and Perinatal Variables on Mutant <i>GATA1</i> Clone Size in Neonates with Down Syndrome

    , BLOOD, Vol: 124, ISSN: 0006-4971
  • Journal article
    Evangelou M, Smyth DJ, Fortune MD, Burren OS, Walker NM, Guo H, Onengut-Gumuscu S, Chen W-M, Concannon P, Rich SS, Todd JA, Wallace Cet al., 2014,

    A Method for Gene-Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

    , GENETIC EPIDEMIOLOGY, Vol: 38, Pages: 661-670, ISSN: 0741-0395
  • Journal article
    MacLean AL, Filippi S, Stumpf MPH, 2014,

    The ecology in the hematopoietic stem cell niche determines the clinical outcome in chronic myeloid leukemia

  • Journal article
    Liepe J, Kirk P, Filippi S, Toni T, Barnes CP, Stumpf MPHet al., 2014,

    A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation

    , NATURE PROTOCOLS, Vol: 9, Pages: 439-456, ISSN: 1754-2189
  • Journal article
    Cohen EAK, Ober RJ, 2013,

    Analysis of point based image registration errors with applications in single molecule microscopy

    , IEEE Transactions on Signal Processing, Vol: 61, Pages: 6291-6306, ISSN: 1053-587X

    We present an asymptotic treatment of errors involvedin point-based image registration where control point (CP)localization is subject to heteroscedastic noise; a suitable modelfor image registration in fluorescence microscopy. Assuming anaffine transform, CPs are used to solve a multivariate regressionproblem. With measurement errors existing for both sets of CPsthis is an errors-in-variable problem and linear least squaresis inappropriate; the correct method being generalized leastsquares. To allow for point dependent errors the equivalence of ageneralized maximum likelihood and heteroscedastic generalizedleast squares model is achieved allowing previously publishedasymptotic results to be extended to image registration. For aparticularly useful model of heteroscedastic noise where covariancematrices are scalar multiples of a known matrix (includingthe case where covariance matrices are multiples of the identity)we provide closed form solutions to estimators and derive theirdistribution. We consider the target registration error (TRE) anddefine a new measure called the localization registration error(LRE) believed to be useful, especially in microscopy registrationexperiments. Assuming Gaussianity of the CP localization errors,it is shown that the asymptotic distribution for the TRE and LREare themselves Gaussian and the parameterized distributions arederived. Results are successfully applied to registration in singlemolecule microscopy to derive the key dependence of the TRE andLRE variance on the number of CPs and their associated photoncounts. Simulations show asymptotic results are robust for lowCP numbers and non-Gaussianity. The method presented here isshown to outperform GLS on real imaging data.

  • Journal article
    Liepe J, Filippi S, Komorowski ML, Stumpf MPHet al., 2013,

    Maximizing the Information Content of Experiments in Systems Biology

    , PLoS computational biology
  • Journal article
    Roy A, Cowan G, Mead AJ, Filippi S, Bohn G, Chaidos A, Tunstall O, Chan JKY, Choolani M, Bennett P, Kumar S, Atkinson D, Wyatt-Ashmead J, Hu M, Stumpf MPH, Goudevenou K, O Connor D, Chou ST, Weiss MJ, Karadimitris A, Jacobsen SE, Vyas P, Roberts Iet al., 2012,

    Perturbation of fetal liver hematopoietic stem and progenitor cell development by trisomy 21.

    , Proceedings of the National Academy of Sciences

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