Outputs (25)

Peptide refinement using a stochastic search (2018)
Journal Article
Lewis, N. H., Hitchcock, D. B., Dryden, I. L., & Rose, J. R. (in press). Peptide refinement using a stochastic search. Journal of the Royal Statistical Society: Series C, https://doi.org/10.1111/rssc.12280

Identifying a peptide based on a scan from a mass spectrometer is an important yet highly challenging problem. To identify peptides, we present a Bayesian approach which uses prior information about the average relative abundances of bond cleavages a... Read More about Peptide refinement using a stochastic search.

Multiple linear regression modelling to predict the stability of polymer-drug solid dispersions: comparison of the effects of polymers and manufacturing methods on solid dispersion stability (2018)
Journal Article
Fridgeirsdottir, G., Harris, R., Dryden, I. L., Fischer, P. M., & Roberts, C. J. (2018). Multiple linear regression modelling to predict the stability of polymer-drug solid dispersions: comparison of the effects of polymers and manufacturing methods on solid dispersion stability. Molecular Pharmaceutics, 15(5), https://doi.org/10.1021/acs.molpharmaceut.8b00021

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two m... Read More about Multiple linear regression modelling to predict the stability of polymer-drug solid dispersions: comparison of the effects of polymers and manufacturing methods on solid dispersion stability.

Journeys in big data statistics (2018)
Journal Article
Dryden, I. L., & Hodge, D. J. (2018). Journeys in big data statistics. Statistics and Probability Letters, 136, https://doi.org/10.1016/j.spl.2018.02.013

The realm of big data is a very wide and varied one. We discuss old, new, small and big data, with some of the important challenges including dealing with highly-structured and object-oriented data. In many applications the objective is to discern pa... Read More about Journeys in big data statistics.

The decomposition of deformation: new metrics to enhance shape analysis in medical imaging (2018)
Journal Article
Varano, V., Piras, P., Gabriele, S., Teresi, L., Nardinocchi, P., Dryden, I. L., Torromeo, C., & Puddu, P. E. (in press). The decomposition of deformation: new metrics to enhance shape analysis in medical imaging. Medical Image Analysis, 46, https://doi.org/10.1016/j.media.2018.02.005

In landmarks-based Shape Analysis size is measured, in most cases, with Centroid Size. Changes in shape are decomposed in affine and non affine components. Furthermore the non affine component can be in turn decomposed in a series of local deformatio... Read More about The decomposition of deformation: new metrics to enhance shape analysis in medical imaging.

Penalised Euclidean distance regression (2018)
Journal Article
Vasiliu, D., Dey, T., & Dryden, I. L. (2018). Penalised Euclidean distance regression. Stat, 7(1), Article e175. https://doi.org/10.1002/sta4.175

A method is introduced for variable selection and prediction in linear regression problems where the number of predictors can be much larger than the number of observations. The methodology involves minimising a penalised Euclidean distance, where th... Read More about Penalised Euclidean distance regression.

Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates: Decoding fMRI Events in SMN (2017)
Journal Article
Tan, F. M., Caballero-Gaudes, C., Mullinger, K. J., Cho, S.-Y., Zhang, Y., Dryden, I. L., Francis, S. T., & Gowland, P. A. (2017). Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates: Decoding fMRI Events in SMN. Human Brain Mapping, 38(11), 5778-5794. https://doi.org/10.1002/hbm.23767

Most functional MRI (fMRI) studies map task-driven brain activity using a block or event-related paradigm. Sparse paradigm free mapping (SPFM) can detect the onset and spatial distribution of BOLD events in the brain without prior timing information,... Read More about Decoding fMRI events in sensorimotor motor network using sparse paradigm free mapping and activation likelihood estimates: Decoding fMRI Events in SMN.

The TPS Direct Transport: a new method for transporting deformations in the Size-and-shape Space (2017)
Journal Article
Varano, V., Gabriele, S., Teresi, L., Dryden, I. L., Puddu, P. E., Torromeo, C., & Piras, P. (in press). The TPS Direct Transport: a new method for transporting deformations in the Size-and-shape Space. International Journal of Computer Vision, https://doi.org/10.1007/s11263-017-1031-9

Modern shape analysis allows the fine comparison of shape changes occurring between different objects. Very often the classic machineries of Generalized Procrustes Analysis and Principal Component Analysis are used in order to contrast the shape chan... Read More about The TPS Direct Transport: a new method for transporting deformations in the Size-and-shape Space.

Covariance analysis for temporal data, with applications to DNA modelling (2017)
Journal Article
Dryden, I. L., Hill, B. C., Wang, H., & Laughton, C. A. (2017). Covariance analysis for temporal data, with applications to DNA modelling. Stat, 6(1), 218-230. https://doi.org/10.1002/sta4.149

We introduce methodology for analysing the mean size-and-shape and covariance matrix of landmark data that are collected over time. Motivated by a study of DNA damage, we study some permutation based tests for investigating significant differences in... Read More about Covariance analysis for temporal data, with applications to DNA modelling.

Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics (2015)
Journal Article
Zhou, D., Dryden, I. L., Koloydenko, A. A., Audenaert, K. M., & Bai, L. (2016). Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics. Journal of Applied Statistics, 43(5), 943-978. https://doi.org/10.1080/02664763.2015.1080671

Practical statistical analysis of diffusion tensor images is considered, and we focus primarily on methods that use metrics based on Euclidean distances between powers of diffusion tensors. First we describe a family of anisotropy measures based on a... Read More about Regularisation, interpolation and visualisation of diffusion tensor images using non-Euclidean statistics.

Bayesian registration of functions and curves (2015)
Journal Article
Cheng, W., Dryden, I. L., & Huang, X. (2015). Bayesian registration of functions and curves. Bayesian Analysis, 2015, https://doi.org/10.1214/15-BA957

Bayesian analysis of functions and curves is considered, where warping and other geometrical transformations are often required for meaningful comparisons. The functions and curves of interest are represented using the recently introduced square root... Read More about Bayesian registration of functions and curves.