Mirela Domijan, Paul E.Brown, Boris V. Shulgin and David A. Rand
Ward, D.G., Baxter, L., Gordon, N.S., Ott, S., Savage, R.S., Beggs, A.D., James, J.D., Lickiss, J., Green, S., Wallis, Y. and Wei, W.
Richard S. Savage, Yinyin Yuan
J. A. Covington, M.P. van. der Schee, A.S.L. Edge, B. Boyle, R.S. Savage and R. P. Arasaradnam
Usman Ahmed, Attia Anwar, Richard S. Savage, Matthew L. Costa, Nicola Mackay, Andrew Filer, Karim Raza, Richard A. Watts, Paul G. Winyard, Joanna Tarr, Richard C. Haigh, Paul J. Thornalley & Naila Rabbani
Non-Invasive Distinction of Non-Alcoholic Fatty Liver Disease using Urinary Volatile Organic Compound Analysis: Early Results
Ramesh P. Arasaradnam1,4, Michael McFarlane1, Emma Daulton2, Erik Westenbrink2, Nicola O'Connell1, Subiatu Wurie1, Chuka U. Nwokolo1, Karna D. Bardhan3, Richard S. Savage5, 6, James A. Covington2
Lloyd, Katherine L., Ian A. Cree, and Richard S. Savage
We present a methodology for dealing with recent challenges in testing global hypotheses using multivariate observations. The proposed tests target situations, often arising in emerging applications of neuroimaging, where the sample size n is relatively small compared with the observations’ dimension K. We employ adaptive designs allowing for sequential modifications of the test statistics adapting to accumulated data. The adaptations are optimal in the sense of maximizing the predictive power of the test at each interim analysis while still controlling the Type I error. Optimality is obtained by a general result applicable to typical adaptive design settings. Further, we prove that the potentially high-dimensional design space of the tests can be reduced to a low-dimensional projection space enabling us to perform simpler power analysis studies, including comparisons to alternative tests. We illustrate the substantial improvement in efficiency that the proposed tests can make over standard tests, especially in the case ofn smaller or slightly larger than K. The methods are also studied empirically using both simulated data and data from an EEG study, where the use of prior knowledge substantially increases the power of the test.
Student Publication, Systems Biology: The proliferating cell hypothesis
The proliferating cell hypothesis: a metabolic framework for Plasmodium growth and development
J. Enrique Salcedo-Sora, Eva Caamano-Gutierrez, Stephen A. Ward, Giancarlo A. Biagini
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool , L3 5QA, UK
- Warwick Systems Biology Centre, Senate House, University of Warwick, Coventry , CV4 7AL, UK
Evgeny Zatulovskiy, Richard Tyson, Till Bretschneider, and Robert R. Kay
Journal of Cell Biology, doi: 10.1083/jcb.201306147, 2014
Sirinukunwattana K., Savage R., Bari M., Snead D., Rajpoot N., 2013, PLOS ONE
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data.
The implementation of GBHC is available at https://sites.google.com/site/gaussianbhc/
Network balance via CRY signalling controls the Arabidopsis circadian clock over ambient temperatures
P.D. Gould*, N. Ugarte*, M. Domijan*, M.J. Costa, J. Foreman, D. McGregor, S. Penfield, D.A. Rand, A. Hall, K. Halliday, A.J. Millar, (2013) , Mol. Syst. Biol. 9(650). DOI:10.1038/msb.2013.7 (F1000prime recommended)
Extracting regulator activity profiles by integration of de novo motifs and expression data: characterizing key regulators of nutrient depletion responses in Streptomyces coelicolor
Determining transcriptional regulator activities is a major focus of systems biology, providing key insight into regulatory mechanisms and co-regulators. For organisms such as Escherichia coli, transcriptional regulator binding site data can be integrated with expression data to infer transcriptional regulator activities. However, for most organisms there is only sparse data on their transcriptional regulators, while their associated binding motifs are largely unknown. Here, we address the challenge of inferring activities of unknown regulators by generating de novo (binding) motifs and integrating with expression data. We identify a number of key regulators active in the metabolic switch, including PhoP with its associated directed repeat PHO box, candidate motifs for two SARPs, a CRP family regulator, an iron response regulator and that for LexA. Experimental validation for some of our predictions was obtained using gel-shift assays. Our analysis is applicable to any organism for which there is a reasonable amount of complementary expression data and for which motifs (either over represented or evolutionary conserved) can be identified in the genome.
Brown, P., Baxter, L., Hickman, R., Beynon, J., Moore, J.D. and Ott, S. (2013) Bioinformatics, doi: 10.1093/bioinformatics/btt248.
A Local Regulatory Network Around Three NAC Transcription Factors in Stress Responses and Senescence in Arabidopsis leaves
Hickman, R., Hill, C., Penfold, C.A., Breeze, E., Bowden, L., Moore, J.D., Zhang, P., Jackson, A., Cooke, E., Bewicke-Copley, F., Mead, A., Beynon, J., Wild, D.L., Denby, K.J., Ott, S. and Buchanan-Wollaston, V. (2013). The Plant Journal, 04/2013.
Quantitative analysis of human ras localization and function in the fission yeast Schizosaccharomyces pombe
Bond M, Croft W, Tyson R, Bretschneider T, Davey J, Ladds G.
Yeast. 2013 Apr;30(4):145-56. doi: 10.1002/yea.2949. Epub 2013 Mar 20.
Traka, M. H., Saha, S., Huseby, S., Kopriva, S., Walley, P. G., Barker, G., Moore, J., Mero, G., van den Bosch, F., Constant, H., Kelly, L., Schepers, H., Boddupalli, S., and Mithen, R. F. (2013). Genetic regulation of glucoraphanin accumulation in Beneforté® broccoli. New Phytologist, doi: 10.1111/nph.12232
Robert Darkins, Emma J Cooke, Zoubin Ghahramani, Paul D.W. Kirk, David L. Wild, Richard S. Savage, PLOS ONE (2013)
Dafyd J. Jenkins, Barbel Finkenstadt and David A. Rand. (2013) Bioinformatics (online ahead of print)
Kirk, P., Griffin, J.E., Savage, R.S., Ghahramani, Z. and Wild, D.L. Bioinformatics (2012) 28 (24): 3290-3297.
Nikolas S. Burkoff, Csilla Várnai and David L. Wild. (2013) Bioinformatics (online ahead of print), 29(1).
Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants
Kitchen, J.L., Moore, J.D., Palmer, S.A. and Allaby, R.G. (2012) MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo sampling. BMC Bioinformatics, 13:287
Arabidopsis Defense against Botrytis cinerea: Chronology and Regulation Deciphered by High-Resolution Temporal Transcriptomic Analysis
Windram, O., Madhou, P., McHattie, S., Hill, C., Hickman, R., Cooke, E., Jenkins, D.J., Penfold, C.A., Baxter, L., Breeze, E., Kiddle, S.J., Rhodes, J., Atwell, S., Klieberstein, D.J., Kim Y-S., Stegle, O., Borgwardt, K., Zhang, C., Tabrett, A., Legaie, R., Moore, J., Finkenstadt, B., Wild, D.L., Mead, A., Rand, D., Beynon, J., Ott, S, Buchanan-Wollaston, V. and Denby, K. (2012) Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis. The Plant Cell, 24(9): 3530-3557.
Evolution of resource and energy management in biologically realistic gene regulatory network models
Stekel DJ and Jenkins DJ (2012). In 'Evolutionary Systems Biology'. Series: Advances in Experimental Medicine and Biology 751, Springer. Chapter 14:301-328
Extracting Fluorescent Reporter Time Courses of Cell Lineages from High-Throughput Microscopy at Low Temporal Resolution
Mike J. Downey, Danuta M. Jeziorska, Sascha Ott, T. Katherine Tamai, Georgy Koentges, Keith W. Vance, Till Bretschneider, 2011, PLoS ONE 6(12): e27886.
2011 PLoS Computational Biology 7(10)
Mukhtar, M.S., Carvunis, A-R., Dreze, M., Epple, P., Steinbrenner, J., Moore, J., Tasan, M., Galli, M., Hao, T., Nishimura, M.T., Pevzner, S.J., Donovan, S.E., Ghamsari, L., Santhanam, B., Romero, V., Poulin, M.M., Gebreab, F., Gutierrez, B.J., Tam, S., Monachello, D., Boxem, M., Harbort, C.J., McDonald, N., Gai, L., Chen, H., He, Y., European Union Effectoromics Consrtium, Vandenhaute, J., Roth, F.P., Hill, D.E., Ecker, J.R., Vidal, M., Beynon, J., Braun, P., Dangl, J.L. (2011) Independently evolved virulence effectors converge onto hubs in a plant immune system network. Science 333(6042): 596-601.
Arabidopsis Interactome Mapping Consortium (2011) Evidence for network evolution in an Arabidopsis interactome map. Science 333(6042): 601-607.
High-Resolution Temporal Profiling of Transcripts during Arabidopsis Leaf Senescence Reveals a Distinct Chronology of Processes and Regulation
Breeze, E., Harrison, E., McHattie, S., Hughes, L., Hickman, R., Hill, C., Kiddle, S., Kim, Y-S., Penfold, C.A., Jenkins, D., Zhang, C., Morris, K., Jenner, C., Jackson, S., Thomas, B., Tabrett, A., Legaie, R., Moore, J.D., Wild, D.L., Ott, S., Rand, D., Beynon, J., Denby, K., Mead, A. and Buchanan-Wollaston, V. (2011) The Plant Cell 23 (3): 873-894.
Laura Baxter, Sucheta Tripathy, Naveed Ishaque, Nico Boot, Adriana Cabra, Eric Kemen, Marco Thines, Audrey Ah-Fong, Ryan Anderson, Wole Badejoko, Peter Bittner-Eddy, Jeffrey L. Boore, Marcus C. Chibucos, Mary Coates, Paramvir Dehal, Kim Delehaunty, Suomeng Dong, Polly Downton, Bernard Dumas, Georgina Fabro, Catrina Fronick, Susan I. Fuerstenberg, Lucinda Fulton, Elodie Gaulin, Francine Govers, Linda Hughes, Sean Humphray, Rays H. Y. Jiang, Howard Judelson, Sophien Kamoun, Kim Kyung, Harold Meijer, Patrick Minx, Paul Morris, Joanne Nelson, Vipa Phuntumart, Dinah Qutob, Anne Rehmany, Alejandra Rougon-Cardoso, Peter Ryden, Trudy Torto-Alalibo, David Studholme, Yuanchao Wang, Joe Win, Jo Wood, Sandra W. Clifton, Jane Rogers, Guido Van den Ackerveken, Jonathan D. G. Jones, John M. McDowell, Jim Beynon, and Brett M. Tyler. Signatures of Adaptation to Obligate Biotrophy in the Hyaloperonospora arabidopsidis Genome. Science 330:6010 pp. 1549-1551
Interactive segmentation of clustered cells via geodesic commute distance and constrained density weighted Nyström method
Du, C.-J., Marcello, M., Spiller, D. G., White, M. R. H. and Bretschneider, T. , Interactive segmentation of clustered cells via geodesic commute distance and constrained density weighted Nyström method. Cytometry Part A, n/a. doi: 10.1002/cyto.a.20993, 2010
Edwards, K. D., Akman, O. E., Knox, K., Lumsden, P. J., Thomson, A. W., Brown, P. E., Pokhilko, A., Kozma-Bognar, L., Nagy, F., Rand, D. A., & Millar, A. J. (2010). Molecular Systems Biology 6:424 doi:10.1038/msb.2010.81
Dafyd J. Jenkins and Dov J. Stekel (2010). Journal of Molecular Evolution 71(2):128-140
Stochasticity Versus Determinism: Consequences for Realistic Gene Regulatory Network Modelling and Evolution
Dafyd J. Jenkins and Dov J. Stekel (2010). Journal of Molecular Evolution 70(2):215-231
On reverse engineering of gene interaction networks using time course data with repeated measurements
Discovering transcriptional modules by Bayesian data integration
Multiquantal release underlies the distribution of synaptic efﬁcacies in the neocortex
Dynamics of populations and networks of neurons with voltage-activated and calcium-activated currents
Extracting nonlinear integrate-and-fire models from experimental data using dynamic I-V curves
Spike-train spectra and network response functions for non-linear integrate-and-fire neurons
Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive
Measurement and analysis of postsynaptic potentials using a novel voltage-deconvolution method
Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces
Badel L, Lefort S, Brette R, Petersen CC, Gerstner W and Richardson MJE. Journal of Neurophysiology 99: 656-666 (2008)
Inferring Transcriptional Networks Using Prior Biological Knowledge and Constrained State-Space Models
R/BHC: Fast Bayesian Hierarchical Clustering for Microarray Data
Computational approaches to the integration of gene expression, ChIP-chip and sequence data in the inference of gene regulatory networks
Reconstruction and stability of secondary structure elements in the context of protein structure prediction
A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series
Modeling and Visualizing Uncertainty in Gene Expression Clusters using Dirichlet Process Mixtures
An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching
CRANKITE A Fast Polypeptide Backbone Conformation Sampler
Comment on: Efficient Monte Carlo trial moves for polypeptide simulations
Hassani-Pak, K., Legaie, R., Canevet, C., van den Berg, H.A., Moore, J.D. and Rawlings, C. (2010) Journal of Integrative Bioinformatics 7:3.
Mohammad T Alam, Maria E Merlo, The STREAM Consortium, David A Hodgson, Elizabeth MH Wellington, Eriko Takano, Rainer Breitling (2010). BMC Genomics 11:202.
Nieselt, K., Battke, F., Herbig, A., Bruheim, P., Wentzel, A., Jakobsen, O.M., Sletta, H., Alam, M.T., Merlo, M.E., Moore, J., Omara,W., Morrissey, E.R., Juarez-Hermosillo, M., Rodríguez-García, A., Nentwich, M., Thomas, L., Legaie, R., Gaze, W.H., Challis, G.L., Jansen, R.C., Dijkhuizen, L., Rand, D.A., Wild, D.L., Bonin, M., Reuther, J., Wohlleben, W., Smith, M.C.M., Burroughs, N.J., Martín, J.F., Hodgson, D.A., Takano, E., Breitling, R., Ellingsen, T.E., Elizabeth M. H. Wellington, E.M.H. (2010). BMC Genomics 11:10. (Highly Accessed Paper)
Archaeogenetic Evidence of Ancient Nubian Barley Evolution from Six to Two-Row Indicates Local Adaptation
Alix, K., Joets, J., Ryder, C.D., Moore, J., Barker, G.C., Bailey, J.P., King, G.J. and Heslop-Harrison, J.S. (2008). The Plant Journal 56: 1030-1044.
R.A. Tyson, D.B.A. Epstein, K.I. Anderson, T. Bretschneider, Math. Model. Nat. Phenom., 5(1):34-55, 2010.
S. Whitelam, T. Bretschneider, N.J. Burroughs, Physical Review Letters, 102:198103, 2009.
Analysis of cell movement by simultaneous quantification of local membrane displacement and fluorescent intensities using Quimp2
L. Bosgraaf, P.J.M. van Haastert, T. Bretschneider, Cell Motility and the Cytoskeleton, 66(3):156-165, 2009.
T. Bretschneider, K. Anderson, M. Ecke, A. Müller-Taubenberger, B. Schroth-Diez, H.C. Ishikawa-Ankerhold, G. Gerisch, Biophys. J., 96, 2888-2900, 2009.
Using single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression.
Dual positive and negative regulation of GPCR signaling by GTP Hydrolysis.
B. Smith, C. Hill, L. Godfrey, D A Rand, H van den Berg, S Thornton, M Hodgkin, J Davey and G Ladds. Cellular Signalling 21 (209)1151-1160 doi:10.1016/j.cellsig.2009.03.00
Bayesian inference of biochemical kinetic parameters using the linear noise approximation.
Network control analysis for time-dependent dynamical states.
Pulsatile stimulation determines timing and specificity of NF-kappa B-dependent transcription.
Steven J. Kiddle, Oliver P. F. Windram, Stuart McHattie, Andrew Mead, Jim Beynon, Vicky Buchanan-Wollaston, Katherine J. Denby and Sach Mukherjee (2010) Bioinformatics 26 (3):355
Prediction of photoperiodic regulators from quantitative gene circuit models.
Moore, J.D., Kell, S.P., Iriondo J, Ford-Lloyd, B. and Maxted, N. (2008) CWRML: representing crop wild relative conservation and use data in XML. BMC Bioinformatics 9:116.
Reversal of cell polarity and actin-myosin cytoskeleton reorganization under mechanical and chemical stimulation.
J. Dalous, E. Burghardt, A. Müller-Taubenberger, F. Bruckert, G. Gerisch, T. Bretschneider. Reversal of cell polarity and actin-myosin cytoskeleton reorganization under mechanical and chemical stimulation. Biophys. J., 94(3):1063-1074, 2008.
Moore, J.D. and Allaby, R.G. (2008) TreeMos: a high-throughput phylogenomic approach to find and visualise phylogenetic mosaicism. Bioinformatics 24(5):717-718.
TreeMos is a novel high-throughput graphical analysis application that allows the user to search for phylogenetic mosaicism among one or more DNA or protein sequence multiple alignments and additional unaligned sequences.
Stochastic niche structure and diversity maintenance in the T cell repertoire.
The Malthusian parameter in microbial ecology and evolution: An optimal control treatment.
The development of insulin resistance in Type 2 diabetes: insights from knockout studies.
R. Pattaranit, H. A. van den Berg, D. Spanswick. The development of insulin resistance in Type 2 diabetes: insights from knockout studies. Sci Prog 91 (2008) 285-316.