2022

Willett, B. J. et al. (2022) SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nature Microbiology, 7(8), pp. 1161-1179. (doi: 10.1038/s41564-022-01143-7) (PMID:35798890) (PMCID:PMC9352574)

Boss, A. N. et al. (2022) Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers. International Journal of Molecular Sciences, 23(13), 7260. (doi: 10.3390/ijms23137260) (PMID:35806273) (PMCID:PMC9266863)

Jones, K.A., Small, A.D., Ray, S. , Hamilton, D.J. , Martin, W., Robinson, J., Goodfield, N.E.R. and Paterson, C.A. (2022) Radionuclide ventriculography phase analysis for risk stratification of patients undergoing cardiotoxic cancer therapy. Journal of Nuclear Cardiology, 29(2), pp. 581-589. (doi: 10.1007/s12350-020-02277-z) (PMID:32748278)

2021

Mamalakis, M., Swift, A. J., Vorselaars, B., Ray, S. , Weeks, S., Ding, W., Clayton, R. H., Mackenzie, L. S. and Banerjee, A. (2021) DenResCov-19: a deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. Computerized Medical Imaging and Graphics, 94, 102008. (doi: 10.1016/j.compmedimag.2021.102008) (PMCID:PMC8539634)

Mackenzie, L. S., Wilkie, C., Ray, S. , Banerjee, A., Mamalakis, M., Swift, A. J., Vorselaars, B., Fanstone, J. and Weeks, S. (2021) Can Kidney Function Be Used to Predict Survival of COVID-19 in Hospitals? Predictive Modelling in a Retrospective Cohort Study. Pharmacology 2021: Today's Science, Tomorrow's Medicines, 07-09 Sep 2021.

2020

Banerjee, A., Ray, S. , Vorselaars, B., Kitson, J., Mamalakis, M., Weeks, S., Baker, M. and Mackenzie, L. S. (2020) Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population. International Immunopharmacology, 86, 106705. (doi: 10.1016/j.intimp.2020.106705) (PMCID:PMC7296324)

2019

Al Alawi, M., Ray, S. and Gupta, M. (2019) A New Framework for Distance-based Functional Clustering. In: 34th International Workshop on Statistical Modelling, Guimarães, Portugal, 07-12 Jul 2019,

Bayarri, M.J., Berger, J. O., Jang, W., Ray, S. , Pericchi, L. R. and Visser, I. (2019) Prior-based Bayesian information criterion. Statistical Theory and Related Fields, 3(1), pp. 2-13. (doi: 10.1080/24754269.2019.1582126)

Berger, J., Jang, W., Ray, S. , Rericchi, L. R. and Visser, I. (2019) Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser. Statistical Theory and Related Fields, 3(1), pp. 37-39. (doi: 10.1080/24754269.2019.1611147)

Ray, S. (2019) Analysis of PET Imaging for Tumor Delineation. 11th SINAPSE Annual Scientific Meeting, Dundee, UK, 21 Jun 2019.

Mangisa, S., Das, S., Ray, S. and Sharp, G. (2019) Functional regression models for South African economic indicators: a growth curve perspective. OPEC Energy Review, 43(2), pp. 217-237. (doi: 10.1111/opec.12148)

2018

Young, D. M., Parry, L. E. , Lee, D. and Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands. PLoS ONE, 13(9), e0202691. (doi: 10.1371/journal.pone.0202691) (PMID:30192790) (PMCID:PMC6128521)

2017

Liu, C., Ray, S. and Hooker, G. (2017) Functional principal component analysis of spatially correlated data. Statistics and Computing, 27(6), pp. 1639-1654. (doi: 10.1007/s11222-016-9708-4)

Labrosse, N. et al. (2017) Preparing for the Journey: Supporting Students to Make Successful Transitions Into and Out of Taught Postgraduate Study. 10th Annual University of Glasgow Learning and Teaching Conference, Glasgow, UK, 30 Mar 2017.

2014

Cheng, Y. and Ray, S. (2014) Parallel and hierarchical mode association clustering with an R package Modalclust. Open Journal of Statistics, 4(10), pp. 826-836. (doi: 10.4236/ojs.2014.410078)

Cheng, Y. and Ray, S. (2014) Multivariate modality inference using Gaussian kernel. Open Journal of Statistics, 4(5), pp. 419-434. (doi: 10.4236/ojs.2014.45041)

Lindsay, B. G., Markatou, M. and Ray, S. (2014) Kernels, degrees of freedom and power properties of quadratic distance goodness of fit tests. Journal of the American Statistical Association, 109(505), pp. 395-410. (doi: 10.1080/01621459.2013.836972)

Bollen, K. A., Harden, J. J., Ray, S. and Zavisca, J. (2014) BIC and alternative Bayesian information criteria in the selection of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 21(1), pp. 1-19. (doi: 10.1080/10705511.2014.856691)

Cheng, Y., Ray, S. , Chang, M. and Menon, S. (2014) Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value. Statistics in Biopharmaceutical Research, 6(3), pp. 241-250. (doi: 10.1080/19466315.2014.923324)

2013

Alexandrovich, G., Holzmann, H. and Ray, S. (2013) On the number of modes of finite mixtures of elliptical distributions. In: Lausen, B., Van den Poel, D. and Ultsch, A. (eds.) Algorithms from and for Nature and Life: Classification and Data Analysis. Series: Studies in Classification, Data Analysis, and Knowledge Organization, 2. Springer International Publishing, pp. 49-57. ISBN 9783319000350 (doi: 10.1007/978-3-319-00035-0_4)

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer. (doi: 10.1111/j.1467-9876.2012.01066.x).

2012

Gupta, M. and Ray, S. (2012) Sequence pattern discovery with applications to understanding gene regulation and vaccine design. In: Rao, C.R., Chakraborty, R. and Sen, P.K. (eds.) Handbook of Statistics. Elsevier Press.

Bollen, K.A., Ray, S. , Zavisca, J. and Harden, J.J. (2012) A comparison of Bayes factor approximation methods including two new methods. Sociological Methods and Research, 41(2), pp. 294-324. (doi: 10.1177/0049124112452393)

Liu, C., Ray, S. , Hooker, G. and Friedl, M. (2012) Functional factor analysis for periodic remote sensing data. Annals of Applied Statistics, 6(2), pp. 601-624. (doi: 10.1214/11-AOAS518)

Ray, S. and Pyne, S. (2012) A computational framework to emulate the human perspective in flow cytometric data analysis. PLoS ONE, 7(5), e35693. (doi: 10.1371/journal.pone.0035693)

Ray, S. and Ren, D. (2012) On the upper bound of the number of modes of a multivariate normal mixture. Journal of Multivariate Analysis, 108, 41 - 52. (doi: 10.1016/j.jmva.2012.02.006)

2011

DeLuca, D.S., Marina, O., Ray, S. , Zhang, G.L., Wu, C.J. and Brusic, V. (2011) Data processing and analysis for protein microarrays. Methods in Molecular Biology, 723(7), pp. 337-347. (doi: 10.1007/978-1-61779-043-0_21)

Shi, P., Ray, S. , Zhu, Q. and Kon, M.A. (2011) Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction. BMC Bioinformatics, 12(1), p. 375. (doi: 10.1186/1471-2105-12-375)

2010

Ray, S. (2010) Discussion of "Projection pursuit via white noise matrices" by G. Hui and B. Lindsay. Sankhya B, 72(2), pp. 147-151. (doi: 10.1007/s13571-011-0008-x)

2008

Lin, H., Ray, S. , Tongchusak, S., Reinherz, E.L. and Brusic, V. (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunology, 9(1), p. 8. (doi: 10.1186/1471-2172-9-8)

Lindsay, B.G., Markatou, M., Ray, S. , Yang, K. and Chen, S.-C. (2008) Quadratic distances on probabilities: A unified foundation. Annals of Statistics, 36(2), pp. 983-1006. (doi: 10.1214/009053607000000956)

Ray, S. and Lindsay, B.G. (2008) Model selection in high dimensions: a quadratic-risk-based approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70(1), pp. 95-118. (doi: 10.1111/j.1467-9868.2007.00623.x)

2007

Li, J., Ray, S. and Lindsay, B.G. (2007) A nonparametric statistical approach to clustering via mode identification. Journal of Machine Learning Research: Proceedings Track, 8, pp. 1687-1723.

Levy, J. H., Reinhardt, J. M., Broadhurst, R. E., Ray, S. , Chaney, E. L. and Pizer, S. M. (2007) Signaling local non-credibility in an automatic segmentation pipeline. In: Medical Imaging 2007: Image Processing, San Diego, CA, USA, 17-22 Feb 2007, (doi: 10.1117/12.709015)

Ray, S. and Kepler, T.B. (2007) Amino acid biophysical properties in the statistical prediction of peptide-MHC class I binding. Immunome Research, 3(1), p. 9. (doi: 10.1186/1745-7580-3-9)

2006

Jeong, J., Pizer, S.M. and Ray, S. (2006) Statistics on anatomic objects reflecting inter-object relations. In: 1st MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability, Copenhagen, 1 Oct 2006, pp. 136-145.

2005

Ray, S. and Lindsay, B.G. (2005) The topography of multivariate normal mixtures. Annals of Statistics, 33(5), pp. 2042-2065. (doi: 10.1214/009053605000000417)

2002

Basu, A., Ray, S. , Park, C. and Basu, S. (2002) Improved power in multinomial goodness-of-fit tests. Journal of the Royal Statistical Society: Series D (The Statistician), 51(3), pp. 381-393. (doi: 10.1111/1467-9884.00325)

Articles

Willett, B. J. et al. (2022) SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway. Nature Microbiology, 7(8), pp. 1161-1179. (doi: 10.1038/s41564-022-01143-7) (PMID:35798890) (PMCID:PMC9352574)

Boss, A. N. et al. (2022) Development of a mortality prediction model in hospitalised SARS-CoV-2 positive patients based on routine kidney biomarkers. International Journal of Molecular Sciences, 23(13), 7260. (doi: 10.3390/ijms23137260) (PMID:35806273) (PMCID:PMC9266863)

Jones, K.A., Small, A.D., Ray, S. , Hamilton, D.J. , Martin, W., Robinson, J., Goodfield, N.E.R. and Paterson, C.A. (2022) Radionuclide ventriculography phase analysis for risk stratification of patients undergoing cardiotoxic cancer therapy. Journal of Nuclear Cardiology, 29(2), pp. 581-589. (doi: 10.1007/s12350-020-02277-z) (PMID:32748278)

Mamalakis, M., Swift, A. J., Vorselaars, B., Ray, S. , Weeks, S., Ding, W., Clayton, R. H., Mackenzie, L. S. and Banerjee, A. (2021) DenResCov-19: a deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays. Computerized Medical Imaging and Graphics, 94, 102008. (doi: 10.1016/j.compmedimag.2021.102008) (PMCID:PMC8539634)

Banerjee, A., Ray, S. , Vorselaars, B., Kitson, J., Mamalakis, M., Weeks, S., Baker, M. and Mackenzie, L. S. (2020) Use of machine learning and artificial intelligence to predict SARS-CoV-2 infection from full blood counts in a population. International Immunopharmacology, 86, 106705. (doi: 10.1016/j.intimp.2020.106705) (PMCID:PMC7296324)

Bayarri, M.J., Berger, J. O., Jang, W., Ray, S. , Pericchi, L. R. and Visser, I. (2019) Prior-based Bayesian information criterion. Statistical Theory and Related Fields, 3(1), pp. 2-13. (doi: 10.1080/24754269.2019.1582126)

Berger, J., Jang, W., Ray, S. , Rericchi, L. R. and Visser, I. (2019) Rejoinder by James Berger, Woncheol Jang, Surajit Ray, Luis R. Pericchi and Ingmar Visser. Statistical Theory and Related Fields, 3(1), pp. 37-39. (doi: 10.1080/24754269.2019.1611147)

Mangisa, S., Das, S., Ray, S. and Sharp, G. (2019) Functional regression models for South African economic indicators: a growth curve perspective. OPEC Energy Review, 43(2), pp. 217-237. (doi: 10.1111/opec.12148)

Young, D. M., Parry, L. E. , Lee, D. and Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands. PLoS ONE, 13(9), e0202691. (doi: 10.1371/journal.pone.0202691) (PMID:30192790) (PMCID:PMC6128521)

Liu, C., Ray, S. and Hooker, G. (2017) Functional principal component analysis of spatially correlated data. Statistics and Computing, 27(6), pp. 1639-1654. (doi: 10.1007/s11222-016-9708-4)

Cheng, Y. and Ray, S. (2014) Parallel and hierarchical mode association clustering with an R package Modalclust. Open Journal of Statistics, 4(10), pp. 826-836. (doi: 10.4236/ojs.2014.410078)

Cheng, Y. and Ray, S. (2014) Multivariate modality inference using Gaussian kernel. Open Journal of Statistics, 4(5), pp. 419-434. (doi: 10.4236/ojs.2014.45041)

Lindsay, B. G., Markatou, M. and Ray, S. (2014) Kernels, degrees of freedom and power properties of quadratic distance goodness of fit tests. Journal of the American Statistical Association, 109(505), pp. 395-410. (doi: 10.1080/01621459.2013.836972)

Bollen, K. A., Harden, J. J., Ray, S. and Zavisca, J. (2014) BIC and alternative Bayesian information criteria in the selection of structural equation models. Structural Equation Modeling: A Multidisciplinary Journal, 21(1), pp. 1-19. (doi: 10.1080/10705511.2014.856691)

Cheng, Y., Ray, S. , Chang, M. and Menon, S. (2014) Statistical monitoring of clinical trials with multiple co-primary endpoints using multivariate B-value. Statistics in Biopharmaceutical Research, 6(3), pp. 241-250. (doi: 10.1080/19466315.2014.923324)

Bollen, K.A., Ray, S. , Zavisca, J. and Harden, J.J. (2012) A comparison of Bayes factor approximation methods including two new methods. Sociological Methods and Research, 41(2), pp. 294-324. (doi: 10.1177/0049124112452393)

Liu, C., Ray, S. , Hooker, G. and Friedl, M. (2012) Functional factor analysis for periodic remote sensing data. Annals of Applied Statistics, 6(2), pp. 601-624. (doi: 10.1214/11-AOAS518)

Ray, S. and Pyne, S. (2012) A computational framework to emulate the human perspective in flow cytometric data analysis. PLoS ONE, 7(5), e35693. (doi: 10.1371/journal.pone.0035693)

Ray, S. and Ren, D. (2012) On the upper bound of the number of modes of a multivariate normal mixture. Journal of Multivariate Analysis, 108, 41 - 52. (doi: 10.1016/j.jmva.2012.02.006)

DeLuca, D.S., Marina, O., Ray, S. , Zhang, G.L., Wu, C.J. and Brusic, V. (2011) Data processing and analysis for protein microarrays. Methods in Molecular Biology, 723(7), pp. 337-347. (doi: 10.1007/978-1-61779-043-0_21)

Shi, P., Ray, S. , Zhu, Q. and Kon, M.A. (2011) Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction. BMC Bioinformatics, 12(1), p. 375. (doi: 10.1186/1471-2105-12-375)

Ray, S. (2010) Discussion of "Projection pursuit via white noise matrices" by G. Hui and B. Lindsay. Sankhya B, 72(2), pp. 147-151. (doi: 10.1007/s13571-011-0008-x)

Lin, H., Ray, S. , Tongchusak, S., Reinherz, E.L. and Brusic, V. (2008) Evaluation of MHC class I peptide binding prediction servers: applications for vaccine research. BMC Immunology, 9(1), p. 8. (doi: 10.1186/1471-2172-9-8)

Lindsay, B.G., Markatou, M., Ray, S. , Yang, K. and Chen, S.-C. (2008) Quadratic distances on probabilities: A unified foundation. Annals of Statistics, 36(2), pp. 983-1006. (doi: 10.1214/009053607000000956)

Ray, S. and Lindsay, B.G. (2008) Model selection in high dimensions: a quadratic-risk-based approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70(1), pp. 95-118. (doi: 10.1111/j.1467-9868.2007.00623.x)

Li, J., Ray, S. and Lindsay, B.G. (2007) A nonparametric statistical approach to clustering via mode identification. Journal of Machine Learning Research: Proceedings Track, 8, pp. 1687-1723.

Ray, S. and Kepler, T.B. (2007) Amino acid biophysical properties in the statistical prediction of peptide-MHC class I binding. Immunome Research, 3(1), p. 9. (doi: 10.1186/1745-7580-3-9)

Ray, S. and Lindsay, B.G. (2005) The topography of multivariate normal mixtures. Annals of Statistics, 33(5), pp. 2042-2065. (doi: 10.1214/009053605000000417)

Basu, A., Ray, S. , Park, C. and Basu, S. (2002) Improved power in multinomial goodness-of-fit tests. Journal of the Royal Statistical Society: Series D (The Statistician), 51(3), pp. 381-393. (doi: 10.1111/1467-9884.00325)

Book Sections

Alexandrovich, G., Holzmann, H. and Ray, S. (2013) On the number of modes of finite mixtures of elliptical distributions. In: Lausen, B., Van den Poel, D. and Ultsch, A. (eds.) Algorithms from and for Nature and Life: Classification and Data Analysis. Series: Studies in Classification, Data Analysis, and Knowledge Organization, 2. Springer International Publishing, pp. 49-57. ISBN 9783319000350 (doi: 10.1007/978-3-319-00035-0_4)

Gupta, M. and Ray, S. (2012) Sequence pattern discovery with applications to understanding gene regulation and vaccine design. In: Rao, C.R., Chakraborty, R. and Sen, P.K. (eds.) Handbook of Statistics. Elsevier Press.

Research Reports or Papers

Chanialidis, C. , Craigmile, P., Davies, V. , Dean, N. , Evers, L. , Filiippone, M., Gupta, M. , Ray, S. and Rogers, S. (2013) Discussion of Henning and Liao: How to find an appropriate clustering for mixed type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C. 62, 309-369. Discussion Paper. Springer. (doi: 10.1111/j.1467-9876.2012.01066.x).

Conference or Workshop Item

Mackenzie, L. S., Wilkie, C., Ray, S. , Banerjee, A., Mamalakis, M., Swift, A. J., Vorselaars, B., Fanstone, J. and Weeks, S. (2021) Can Kidney Function Be Used to Predict Survival of COVID-19 in Hospitals? Predictive Modelling in a Retrospective Cohort Study. Pharmacology 2021: Today's Science, Tomorrow's Medicines, 07-09 Sep 2021.

Ray, S. (2019) Analysis of PET Imaging for Tumor Delineation. 11th SINAPSE Annual Scientific Meeting, Dundee, UK, 21 Jun 2019.

Labrosse, N. et al. (2017) Preparing for the Journey: Supporting Students to Make Successful Transitions Into and Out of Taught Postgraduate Study. 10th Annual University of Glasgow Learning and Teaching Conference, Glasgow, UK, 30 Mar 2017.

Conference Proceedings

Al Alawi, M., Ray, S. and Gupta, M. (2019) A New Framework for Distance-based Functional Clustering. In: 34th International Workshop on Statistical Modelling, Guimarães, Portugal, 07-12 Jul 2019,

Levy, J. H., Reinhardt, J. M., Broadhurst, R. E., Ray, S. , Chaney, E. L. and Pizer, S. M. (2007) Signaling local non-credibility in an automatic segmentation pipeline. In: Medical Imaging 2007: Image Processing, San Diego, CA, USA, 17-22 Feb 2007, (doi: 10.1117/12.709015)

Jeong, J., Pizer, S.M. and Ray, S. (2006) Statistics on anatomic objects reflecting inter-object relations. In: 1st MICCAI Workshop on Mathematical Foundations of Computational Anatomy: Geometrical, Statistical and Registration Methods for Modeling Biological Shape Variability, Copenhagen, 1 Oct 2006, pp. 136-145.