Dr Keefe Murphy

    Mathematics and Statistics, Hamilton Institute

    Lecturer

    Logic House
    130
    (01) 708 4641

    Biography

    I am a statistician with primary research interests in developing methodologies for both supervised and unsupervised classification tasks involving complex, high-dimensional, mixed-type data, often in the presence of outliers. Publications to date include work on Bayesian nonparametric mixtures of factor analysers, covariate-dependent parsimonious model-based clustering, and risk-stratification for multi-omic prostate cancer data. I am currently working on applications of novel distance-based clustering approaches for longitudinal categorical sequences. I take a keen interest in the computational implementation of statistical models and have authored the R packages IMIFA, MoEClust, and MEDseq, all of which are available on CRAN.

    Research Interests

    I have a broad range of research interests in the fields of Statistics, Data Science, and Machine Learning including, but not limited to; mixture/latent-variable models, model-based clustering and classification, Bayesian statistics, shrinkage priors, applications to high-dimensional, mixed-type data, computational statistics, dimension reduction, sequence analysis, missing data mechanisms, tree-based methods, non-parametric regression, model selection, model aggregation, and data visualisation. Most of the research projects I have worked on involved a non-trivial computation aspect and I take a keen interest in distributing software implementations of my novel methodologies.

    Peer Reviewed Journals

      Year Publication
    2021 'Clustering longitudinal life-course sequences using mixtures of exponential-distance models'
    Murphy K.;Murphy T.B.;Piccarreta R.;Gormley I.C. (2021) 'Clustering longitudinal life-course sequences using mixtures of exponential-distance models'. Journal of the Royal Statistical Society. Series A, (Statistics in Society), 184 (4):1414-1451 [DOI] [Details]
    2020 'Gaussian parsimonious clustering models with covariates and a noise component'
    Murphy K.;Murphy T.B. (2020) 'Gaussian parsimonious clustering models with covariates and a noise component'. Advances in Data Analysis and Classification, 14 (2):293-325 [DOI] [full-text] [Details]
    2020 'Infinite mixtures of infinite factor analysers'
    Murphy K.;Viroli C.;Gormley I.C. (2020) 'Infinite mixtures of infinite factor analysers'. Bayesian Analysis, 15 (3):937-963 [DOI] [full-text] [Details]
    2018 'Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer'
    Murphy K.;Murphy T.B.;Boyce S.;Flynn L.;Gilgunn S.;O'Rourke C.J.;Rooney C.;Stöckmann H.;Walsh A.L.;Finn S.;O'Kennedy R.J.;O'Leary J.;Pennington S.R.;Perry A.S.;Rudd P.M.;Saldova R.;Sheils O;Shields D.C.;Watson R.W.; (2018) 'Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer'. Molecular Oncology, 12 (9) [DOI] [Details]
    2020 'Glycosylation in Indolent, Significant and Aggressive Prostate Cancer by Automated High-Throughput N-Glycan Profiling'
    Gilgunn, S;Murphy, K;Stockmann, H;Conroy, PJ;Murphy, TB;Watson, RW;O'Kennedy, RJ;Rudd, PM;Saldova, R (2020) 'Glycosylation in Indolent, Significant and Aggressive Prostate Cancer by Automated High-Throughput N-Glycan Profiling'. International Journal of Molecular Sciences, 21 [DOI] [full-text] [Details]
    2020 'A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort'
    Jalali A;Foley RW;Maweni RM;Murphy K;Lundon DJ;Lynch T;Power R;O'Brien F;O'Malley KJ;Galvin DJ;Durkan GC;Murphy TB;Watson RW; (2020) 'A risk calculator to inform the need for a prostate biopsy: a rapid access clinic cohort'. BMC Medical Informatics and Decision Making, 20 (1) [DOI] [full-text] [Details]
    2017 'The role of epithelial-mesenchymal transition drivers ZEB1 and ZEB2 in mediating docetaxel-resistant prostate cancer'
    Hanrahan K;O'Neill A;Prencipe M;Bugler J;Murphy L;Fabre A;Puhr M;Culig Z;Murphy K;Watson RW; (2017) 'The role of epithelial-mesenchymal transition drivers ZEB1 and ZEB2 in mediating docetaxel-resistant prostate cancer'. Molecular Oncology, 11 (3) [DOI] [Details]
    2016 'European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculators significantly outperform the Prostate Cancer Prevention Trial (PCPT) 2.0 in the prediction of prostate cancer: a multi-institutional study'
    Foley RW;Maweni RM;Gorman L;Murphy K;Lundon DJ;Durkan G;Power R;O'Brien F;O'Malley KJ;Galvin DJ;Brendan Murphy T;William Watson R; (2016) 'European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculators significantly outperform the Prostate Cancer Prevention Trial (PCPT) 2.0 in the prediction of prostate cancer: a multi-institutional study'. BJU International, 118 (5) [DOI] [Details]
    2016 'Improving multivariable prostate cancer risk assessment using the Prostate Health Index'
    Foley RW;Gorman L;Sharifi N;Murphy K;Moore H;Tuzova AV;Perry AS;Murphy TB;Lundon DJ;Watson RW; (2016) 'Improving multivariable prostate cancer risk assessment using the Prostate Health Index'. BJU International, 117 (3) [DOI] [Details]
    2015 'Predicting prostate cancer: analysing the clinical efficacy of prostate cancer risk calculators in a referral population'
    Foley RW;Lundon DJ;Murphy K;Murphy TB;Galvin DJ;Watson RW; (2015) 'Predicting prostate cancer: analysing the clinical efficacy of prostate cancer risk calculators in a referral population'. Irish Journal of Medical Science, 184 (3) [DOI] [Details]

    Computer Program

      Year Publication
    2020 MEDseq: Mixtures of Exponential-Distance Models with Covariates.
    Murphy, K.; Murphy, T.B.; Piccarreta, R.; Gormley, I.C. (2020) MEDseq: Mixtures of Exponential-Distance Models with Covariates. Computer Program [Details]
    2020 MoEClust: Gaussian Parsimonious Clustering Models with Covariates and a Noise Component.
    Murphy K.;Murphy T.B. (2020) MoEClust: Gaussian Parsimonious Clustering Models with Covariates and a Noise Component. Computer Program [Details]
    2020 IMIFA: Infinite Mixtures of Infinite Factor Analysers and Related Models.
    Murphy K.;Viroli C.;Gormley I.C. (2020) IMIFA: Infinite Mixtures of Infinite Factor Analysers and Related Models. Computer Program [Details]

    Honours and Awards

      Year Title Awarding Body
    2020 Distinguished Dissertation Award The Classification Society

    Education

      Year Institution Qualification Subject
    2019 University College Dublin Doctor of Philosophy Statistics
    2014 University College Dublin Master of Science Statistics
    2012 University of Limerick Bachelor of Science Economics & Mathematics

    Reviews

      Journal Role
    Advances In Data Analysis And Classification Reviewer
    Annals Of Applied Statistics Reviewer
    Australian And New Zealand Journal Of Statistics Reviewer
    Communications In Statistics Part B: Simulation And Computation Reviewer
    Computational Statistics And Data Analysis Reviewer
    International Journal Of Computer Applications In Technology Reviewer
    Journal Of Computational And Graphical Statistics Reviewer
    Scandinavian Journal Of Statistics Reviewer
    Statistical Analysis And Data Mining Reviewer
    Statistics And Computing Reviewer

    Teaching Interests

    I am currently lecturing modules on Linear Models, Statistical Computing with R, and Nonparametric Statistics. Other courses I have previously taught include Statistical Machine Learning, Stochastic Processes, and Design & Analysis of Experiments.