Ian Dryden is a Professor of Statistics in the School of Mathematical Sciences at the University of Nottingham.
My broad research interests concern the development of generic statistical methodology motivated by important real-world applications. I am particularly interested in geometrical problems, for example the statistical analysis of the shapes of objects. Such data are routinely available in a very wide variety of settings, from the smallest scale of atoms and molecules in chemistry, to the study of complex organisms in biology and medicine.
Ian Dryden’s homepage
Published Work
- Kenobi K, Dryden IL, Le H (2010) Shape curves and geodesic modelling. Biometrika 7, 567–584
- Browne WJ, Dryden IL, Handley K, Mian S, Schadendorf, D (2010) Mixed effect modelling of proteomic mass spectrometry data using Gaussian mixtures. Journal of the Royal Statistical Society, Series C (Applied Statistics) 59, 617–633
- Holman TJ*, Wilson MH*, Kenobi K*, Dryden IL, Hodgman TC, Wood ATA, Holdsworth MJ (2010) Statistical evaluation of transcriptomic data generated using the Affymetrix one-cycle, two-cycle and IVT-Express RNA labelling protocols with the Arabidopsis ATH1 microarray. Plant Methods 6, 9 [*authors contributed equally.]
Virtual Root
- Dryden IL, Kume A, Le H, Wood ATA (2008) Statistical inference for functions of the covariance matrix in the stationary Gaussian time-orthogonal principal components model. Annals of the Institute of Statistical Mathematics 62, 967–994
- Dryden IL, Kume A, Le H, Wood ATA (2008) A multidimensional scaling approach to shape analysis. Biometrika 95, 779–798
- Amaral GJA, Dryden IL, Wood ATA (2007) Pivotal bootstrap methods for k-sample problems in directional statistics and shape analysis. Journal of the American Statistical Association 102, 695–707
- Hodgman TC, Ugartechea-Chirino Y, Tansley G, Dryden I (2006) The implications for bioinformatics of integration across the scales. Journal of Integrative Bioinformatics 3, 39
