STATISTICS OF LARGE DATASETS
Functional and image data, bioinformatics and data mining

Please note that the papers marked * are unavailable electronically.

EXTRA PAGES

Preliminary and final pages including cover, Preface, Contents and Index.

PAPERS

K.V. Mardia and D.R. Westhead. New major challenges in bioinformatics. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 9-15. Department of Statistics, University of Leeds.

G.J. Barton Progress in protein secondary structure prediction. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 21-22. Department of Statistics, University of Leeds.

I.L. Dryden, A. Kume, H. Le, A.T.A. Wood and C.A. Laughton Size-and-shape analysis of DNA molecular dynamics simulations. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 23-26. Department of Statistics, University of Leeds.

M. Coates Interface Developments in Statistical Software. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 27. Department of Statistics, University of Leeds.

* L. Edler and F. Markowetz Classification methods for protein fold prediction: statistical methods, neural networks and support vector machines. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 31-35. Department of Statistics, University of Leeds.

* C.A. Glasbey A comparison of estimators of differential expression in cDNA microarrays. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 37-40. Department of Statistics, University of Leeds.

D.J. Hand Patterns. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 43. Department of Statistics, University of Leeds.

* C.C. Taylor and M. Di Marzio Kernel Density Discrimination. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 45-48. Department of Statistics, University of Leeds.

* F.L. Bookstein Lessons from morphometrics for biological data mining. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 49-53. Department of Statistics, University of Leeds.

V. Patrangenaru, G. Derado and S. Belkasim Estimation of evolution curves in space of images. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 55-58. Department of Statistics, University of Leeds.

S. Di Zio, L. Fontanella and L. Ippoliti Fractal geometry for optimal spatial sampling. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 59-62. Department of Statistics, University of Leeds.

S. Gattone and T. Di Battista Non Parametric Confidence Bands for beta-Diversity Profiles In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 63-66. Department of Statistics, University of Leeds.

* K.V. Mardia, P. McDonnell and A. Linney Image averaging and discrimination In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 67-70. Department of Statistics, University of Leeds.

M.J.K. Gales Adaptive training for large vocabulary speech recognition. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 73-76. Department of Statistics, University of Leeds.

* K.V. Mardia, C.C. Taylor and M. Subramaniam Speech recognition and cepstrum coefficient. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 77-84. Department of Statistics, University of Leeds.

R.G Aykroyd, Sha Meng and R.M. West Deterministic and stochastic approaches to inverse problems. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 85-88. Department of Statistics, University of Leeds.

J.T. Kent and K.V. Mardia Functional data analysis for spatial-temporal data. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 89. Department of Statistics, University of Leeds.

* S. Marsland and C. Twining Clamped-plate splines and the optimal flow of bounded diffeomorphisms. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 91-95. Department of Statistics, University of Leeds.

* B. Silverman Wavelet thresholding and empirical Bayes: Finding both needles and hay in haystacks. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 96. Department of Statistics, University of Leeds.


POSTERS


S.M. Al-Gezeri and R.G. Aykroyd Extensions to the single-layer model for archaeological survey data. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 101-104. Department of Statistics, University of Leeds.

Y.M.T. El Gimati and C.C. Taylor Weighted bagging in decision trees. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 105-108. Department of Statistics, University of Leeds.

F.M.O. Hamed and R.G. Aykroyd. A spline-based approach to linked feature modelling. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 109-112. Department of Statistics, University of Leeds.

J. Illian, E. Benson, H. Staines and J. Crawford The spatial pattern of a natural plant community. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 113-116. Department of Statistics, University of Leeds.

V.G. Krishnan and D.R. Westhead Single nucleotide polymorphisms: novel method to predict their functional effects using machine learning methods. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 117. Department of Statistics, University of Leeds.

* A. Kume, I.L. Dryden, Huiling Le and A.T.A. Wood Fitting cubic splines to data in shape spaces of planar configuration. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 119-122. Department of Statistics, University of Leeds.

V.G. Krishnan and D.R. Westhead Characterising non-uniqueness in L-1 ordinary Procrustes analysis. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 123. Department of Statistics, University of Leeds.

K.S. Mwitondi, C.C. Taylor and J.T. Kent Using boosting in classification. In R.G. Aykroyd, K.V. Mardia and P McDonnell (Eds.), STATISTICS OF LARGE DATASETS: Functional and image data, bioinformatics and data mining, pp. 125-128. Department of Statistics, University of Leeds.