High-throughput Sequencing, Proteins and Statistics

Proceedings of the 29th Leeds Annual Statistical Research Workshop
6th-8th July 2010

This page contains the proceedings of the LASR2010 workshop You can download the complete proceedings volume in one big file:

• LASR2010 proceedings (2.5MB)

• Kanti V. Mardia: Statistical complexity in protein bioinformatics II, pp. 9-16
• Terry Speed, Oleg Mayba: Analysis of ChIP-Seq Data, pp. 17-19
• Ernst Wit, Antonio Abbruzzo: Sparse model-based network inference using Gaussian graphical models, pp. 23-28
• John T. Kent, Kanti V. Mardia, Charles C. Taylor: An EM interpretation of the Softassign algorithm for alignment problems, pp. 29-32
• Fred L. Bookstein: Numbers and reasons — core elements of numerical inference techniques today, with implications for the rhetoric of LASR presentations, pp. 33-38
• Stephan F. Huckemann, Thomas Hotz: Geodesic and parallel models for leaf shape, pp. 39-43
• Arthur M. Lesk: Tableau representation of protein folding patterns, p. 47
• Paul Verrier: Trying to use sums to answer scientific questions raised by Rothamsted's research - some solved, some waiting for a solution, p. 51
• Clive E. Bowman, Chris I. Jones: Genetic evidence-of-no-interest, pathway Sudoku and platelet function, pp. 53-58
• Matthew Care, David R. Westhead: BLIMP1: a bioinformatics led analysis of a key transcription factor, p. 59
• Jonas Paulsen, Martin Paluszewski, Kanti V. Mardia, Thomas Hamelryck: A probabilistic model of hydrogen bond geometry in proteins, pp. 61-64
• Sarah L. Kinnings, Li Xie, Kingston H. Fung, Richard M. Jackson, Lei Xie, Philip E. Bourne: The Mycobacterium tuberculosis drugome and its polypharmacological implications, p. 65
• Geoff J. McLachlan: Clustering of high-dimensional data with application to gene-expression data, pp. 69-73
• Siem H. Heisterkamp: Directed acyclic graphs and the use of linear mixed models, pp. 75-79
• Florian Klinglmueller, Thomas Tuechler, Martin Posch: Cross platform comparison of microarray data using order restricted inference, pp. 81-83
• Wally Gilks: New DNA sequencing technologies: challenges and opportunities, pp. 85-88
• Alessandro Ambrosi, Danilo Pellin, Paolo Miotto, Daniela Cirillo, Clelia Di Serio: A genome-wide identification analysis of small regulatory RNAs in Mycobacterium tuberculosis by RNA-Seq, pp. 91-94
• Suaad O. Benfarag, David Perkins, Charles C. Taylor: Statistical analysis to study the factors that affect the relative intensity of y and b ions produced in MS/MS experiments of protein identification, pp. 95-97
• James R. Bradford, Yvonne Hey, Tim Yates, Yaoyong Li, Stuart D. Pepper, Crispin J. Miller: Global transcription profiling using massively parallel nucleotide sequencing: a comparison with Exon arrays, pp. 98-101
• Riccardo De Bin, Davide Risso: Clustering via nonparametric density estimation: an application to microarray data, pp. 102-105
• Joel P. Dockray, Richard M. Jackson, Thomas A. Edwards: The p53-Mdm2 interaction: predicting helix mimetic side-chain modifications likely to increase inhibitor affinity, pp. 106-107
• Asaad M. Ganeiber, John T. Kent: Saddlepoint Approximations for the Complex Bingham Quartic Distribution, pp. 108-111
• Steven M. Hill, Yiling Lu, Gordon B. Mills, Sach Mukherjee: Dynamic Bayesian analysis of protein signalling connectivity reveals heterogeneity within single breast cancer subtype, p. 112
• Kerstin Hommola, Walter R. Gilks, Kanti V. Mardia: Log-linear modelling of protein dipeptide structure reveals interesting patterns of side-chain—backbone interactions, p. 113
• Jennifer Klapper, Stuart Barber: A multi-scale approach to analysing High Performance Liquid Chromatography data, pp. 114-116
• Yaoyong Li, James Bradford, Crispin J. Miller: Evaluation of statistical methods for exon differential expressions using sequencing data, pp. 117-120
• Kanti V. Mardia, Christopher J. Fallaize, Stuart Barber, Richard M. Jackson, Douglas L. Theobald: Bayesian alignment of unlabelled similarity shapes, p. 121
• K.V. Mardia, J.T. Kent, C.C. Taylor, Z. Zhang, T. Hamelryck: A mixture model of multivariate sine distributions to investigate patterns in the protein data, p. 122
• Joseph Ward: Predicting hot-spots in protein-protein interaction interfaces, p. 123