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PeTTSy: a computational tool for perturbation analysis of complex systems biology models

Mirela Domijan, Paul E.Brown, Boris V. Shulgin and David A. Rand

Fri 18 Mar 2016, 14:18

Multiplex PCR and Next Generation Sequencing for the Non-Invasive Detection of Bladder Cancer

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.

Tue 15 Mar 2016, 09:54


Non-invasive exhaled volatile organic biomarker analysis to detect inflammatory bowel disease (IBD)

Ramesh P. Arasaradnam,
Michael McFarlane,
Emma Daulton,

Jim Skinner, Nicola O’Connell, Subiatu Wurie, Samantha Chambers, Chuka Nwokolo, Karna Bardhan, Richard Savage, James Covington

Tue 05 Jan 2016, 10:51

The application of FAIMS gas analysis in Medical Diagnostics

J. A. Covington, M.P. van. der Schee, A.S.L. Edge, B. Boyle, R.S. Savage and R. P. Arasaradnam

Thu 23 Jul 2015, 08:45

Biomarkers of early stage osteoarthritis, rheumatoid arthritis and musculoskeletal health.

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

Thu 11 Jun 2015, 13:53

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

Tue 09 Jun 2015, 15:56

Rapid, Accurate, and On-Site Detection of C. difficile in Stool Samples

Marije K Bomers, Frederik P Menke, Richard S Savage, Christina M J E Vandenbroucke-Grauls, Michiel A van Agtmael, James A Covington, and Yvo M Smulders

Mon 27 Apr 2015, 15:20

Prediction of resistance to chemotherapy in ovarian cancer: a systematic review

Lloyd, Katherine L., Ian A. Cree, and Richard S. Savage

Thu 19 Mar 2015, 11:55


Differentiating Coeliac Disease from Irritable Bowel Syndrome by Urinary Volatile Organic Compound Analysis – A Pilot Study

  • Ramesh P. Arasaradnam mail,
  • Eric Westenbrink,
  • Michael J. McFarlane,
  • Ruth Harbord,
  • Samantha Chambers,
  • Nicola O’Connell,
  • Catherine Bailey,
  • Chuka U. Nwokolo,
  • Karna D. Bardhan,
  • Richard Savage,
  • James A. Covington
Fri 31 Oct 2014, 10:25

How blebs and pseudopods cooperate during chemotaxis

Richard A. Tyson, Evgeny Zatulovskiy, Robert R. Kay, and Till Bretschneider
PNAS 2014 ; published ahead of print July 29, 2014, doi:10.1073/pnas.1322291111

Fri 08 Aug 2014, 11:52

Adaptive Multivariate Global Testing

Giorgos Minas, John A.D. Aston & Nigel Stallard

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.

Thu 24 Jul 2014, 14:44

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

Trends in Parasitology
Volume 30, Issue 4, pp. 170–175, April 2014
  • Liverpool School of Tropical Medicine, Pembroke Place, Liverpool , L3 5QA, UK
  • Warwick Systems Biology Centre, Senate House, University of Warwick, Coventry , CV4 7AL, UK

http://www.cell.com/trends/parasitology/fulltext/S1471-4922(14)00021-X

Wed 28 May 2014, 11:04 | Tags: student publications

Bleb-driven chemotaxis of Dictyostelium cells

Evgeny Zatulovskiy, Richard Tyson, Till Bretschneider, and Robert R. Kay
Journal of Cell Biology, doi: 10.1083/jcb.201306147, 2014

Wed 12 Mar 2014, 11:20


Discovery of a family of gamma-aminobutyrate ureas via rational derepression of a silent bacterial gene cluster

J.D. Sidda, L. Song, V. Poon, M. Al-Bassam, O. Lazos, M.J. Buttner, G.L. Challis and C. Corre

Chem. Sci.,2014, 5 (1), 86-89.

Fri 20 Dec 2013, 11:49 | Tags: student publications

Bayesian Hierarchical Clustering for Studying Cancer Gene Expression Data with Unknown Statistics

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/

Thu 24 Oct 2013, 15:36

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)

Tue 15 Oct 2013, 14:07

Extracting regulator activity profiles by integration of de novo motifs and expression data: characterizing key regulators of nutrient depletion responses in Streptomyces coelicolor

Iqbal M, Mast Y, Amin R, Hodgson DA; STREAM Consortium, Wohlleben W, Burroughs NJ.

Nucleic Acids Res. (2012) 40 (12): 5227-39. doi: 10.1093/nar/gks205

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.

Thu 10 Oct 2013, 07:14

Making open data work for plant scientists

Leonelli, S., Smirnoff, N., Moore, J., Cook, C. and Bastow, R. (2013) Journal of Experimental Botany 09/2013

Sun 22 Sep 2013, 23:05

MEME-LaB: motif analysis in clusters

Brown, P., Baxter, L., Hickman, R., Beynon, J., Moore, J.D. and Ott, S. (2013) Bioinformatics, doi: 10.1093/bioinformatics/btt248.

Sun 22 Sep 2013, 23:04

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.

Sun 22 Sep 2013, 23:02 | Tags: student publications

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.

 

Wed 01 May 2013, 14:17

Genetic regulation of glucoraphanin accumulation in Beneforté® broccoli

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

Fri 19 Apr 2013, 09:43

Accelerating Bayesian Hierarchical Clustering of Time Series Data with a Randomised Algorithm

Robert Darkins, Emma J Cooke, Zoubin Ghahramani, Paul D.W. Kirk, David L. Wild, Richard S. Savage, PLOS ONE (2013)

Wed 03 Apr 2013, 14:34

A temporal switch model for estimating transcriptional activity in gene expression

Dafyd J. Jenkins, Barbel Finkenstadt and David A. Rand. (2013) Bioinformatics (online ahead of print)

Mon 11 Mar 2013, 10:56

Bayesian correlated clustering to integrate multiple datasets.

Kirk, P., Griffin, J.E., Savage, R.S., Ghahramani, Z. and Wild, D.L. Bioinformatics (2012) 28 (24): 3290-3297.

Tue 15 Jan 2013, 13:48


Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants

Laura Baxter, Aleksey Jironkin, Richard Hickman, Jay Moore, Christopher Barrington, Peter Krusche, Nigel P. Dyer, Vicky Buchanan-Wollaston, Alexander Tiskin, Jim Beynon, Katherine Denby, Sascha Ott (2012), Plant Cell, 24: 3949-3965

toll-free link
press release and video

Wed 05 Dec 2012, 14:04

MCMC-ODPR: Primer design optimization using Markov Chain Monte Carlo sampling

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

Tue 06 Nov 2012, 13:36

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.

Mon 29 Oct 2012, 13:00

Archaeogenomic evidence of punctuated genome evolution in Gossypium

Palmer, S.A., Clapham, A.J., Rose, P., Freitas, F.O., Owen, B.D., Beresford-Jones, D., Moore, J.D., Kitchen, J.L. and Allaby, R.G. (2012) Archaeogenomic evidence of punctuated genome evolution in Gossypium. Molecular Biology and Evolution 29 (8).

Wed 15 Aug 2012, 15:43

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

Mon 30 Jul 2012, 10:05

Modeling Meiotic Chromosomes Indicates a Size Dependent Contribution of Telomere Clustering and Chromosome Rigidity to Homologue Juxtaposition

Christopher A. Penfold, Paul E. Brown, Neil D. Lawrence, Alastair S. H. Goldman, 2012, PLoS Comput Biol 8(5): e1002496. doi:10.1371/journal.pcbi.1002496

Tue 08 May 2012, 10:53

Metabolic switches and adaptations deduced from the proteomes of Streptomyces coelicolor wild type and phoP mutant grown in batch culture

Thomas, L., Hodgson, D.A., Wentzel, A., Nieselt, K., Ellingsen, T.E., Moore. J., Morrissey, E.R., Legaie, R; The STREAM Consortium, Wohleben, W., Rodriguez-Garcia, A., Martin, J.F., Burroughs, N.J., Wellington, E.M., Smith, M.C. (2012) Mol. Cell Proteomics, 11(2): M111.013797.

Sat 03 Mar 2012, 18:49

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.

Tue 10 Jan 2012, 14:18

Patient-Specific Data Fusion Defines Prognostic Cancer Subtypes

Yuan Y, Savage RS (joint 1st author), Markowetz F, 2011 PLoS Computational Biology 7(10)

Fri 21 Oct 2011, 15:12

Independently evolved virulence effectors converge onto hubs in a plant immune system network

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.

Thu 18 Aug 2011, 14:02

Evidence for network evolution in an Arabidopsis interactome map

Arabidopsis Interactome Mapping Consortium (2011) Evidence for network evolution in an Arabidopsis interactome map. Science 333(6042): 601-607.

Fri 29 Jul 2011, 09:51

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.

Fri 29 Apr 2011, 09:24

Nodal cis-regulatory elements reveal epiblast and primitive endoderm heterogeneity in the peri-implantation mouse embryo

Céline Granier, Vasily Gurchenkov, Aitana Perea-Gomez, Anne Camus, Sascha Ott, Costis Papanayotou, Julian Iranzo, Anne Moreau, John Reid, Georgy Koentges, Délara Sabéran-Djoneidi, Jérôme Collignon (2011) Developmental Biology, 349: 350-362

Thu 03 Feb 2011, 22:28

Recombinants between Deformed wing virus and Varroa destructor virus-1 may prevail in Varroa destructor-infested honeybee colonies

Moore, J., Jironkin, A., Chandler, D., Burroughs, N., Evans, D.J. and Ryabov, E.V. (2011) Recombinants between Deformed wing virus and Varroa destructor virus-1 may prevail in Varroa destructor-infested honeybee colonies. Journal of General Virology 92, 156-161.

Mon 17 Jan 2011, 09:42

Signatures of Adaptation to Obligate Biotrophy in the Hyaloperonospora arabidopsidis Genome

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

Tue 14 Dec 2010, 10:25

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

Wed 10 Nov 2010, 17:41

Quantitative analysis of regulatory flexibility under changing environmental conditions

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

Wed 03 Nov 2010, 13:56

De Novo Evolution of Complex, Global and Hierarchical Gene Regulatory Mechanisms

Dafyd J. Jenkins and Dov J. Stekel (2010). Journal of Molecular Evolution 71(2):128-140

Mon 23 Aug 2010, 09:48

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

Mon 23 Aug 2010, 09:46

On reverse engineering of gene interaction networks using time course data with repeated measurements

E.R. Morrissey, M.A. Juárez, K. J. Denby, and N.J Burroughs (2010) . Bioinformatics 26, 2305—2312 (DOI:10.1093/bioinformatics/btq421)
Fri 30 Jul 2010, 12:36

Discovering transcriptional modules by Bayesian data integration

Richard S. Savage; Zoubin Ghahramani; Jim E. Griffin; Bernard J. de la Cruz; David L. Wild Bioinformatics 2010 26: i158-i167
Mon 07 Jun 2010, 15:14

Multiquantal release underlies the distribution of synaptic efficacies in the neocortex

Loebel A, Silberberg G, Helbig D, Markram H, Tsodyks M and Richardson MJE. Frontiers in Computational Neuroscience 3: article-no 27 (2009)
Tue 11 May 2010, 10:51

Dynamics of populations and networks of neurons with voltage-activated and calcium-activated currents

Richardson MJE. Physical Review E 80: article-no 021928 (2009)
Tue 11 May 2010, 10:50

Extracting nonlinear integrate-and-fire models from experimental data using dynamic I-V curves

Badel L, Lefort S, Berger TK, Petersen CC, Gerstner W and Richardson MJE. Biological Cybernetics 99: 361-370 (2008)
Tue 11 May 2010, 10:49

Spike-train spectra and network response functions for non-linear integrate-and-fire neurons

Richardson MJE. Biological Cybernetics 99: 381-392 (2008)
Tue 11 May 2010, 10:47

Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive

Badel L, Gerstner W and Richardson MJE. Physical Review E 78: article-no 011914 (2008)
Tue 11 May 2010, 10:46

Measurement and analysis of postsynaptic potentials using a novel voltage-deconvolution method

Richardson MJE and Silberberg G. Journal of Neurophysiology 99: 1020-1031 (2008)
Tue 11 May 2010, 10:44

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)

Tue 11 May 2010, 10:40

Inferring Transcriptional Networks Using Prior Biological Knowledge and Constrained State-Space Models

Angus, J. Beal, M.J., Li, J., Rangel, C., Wild, D.L. In Lawrence, N.D., Girolami, M., Rattray, M. and Sanguinetti, G. (Eds.), Learning and Inference in Computational Systems Biology, MIT Press, Cambridge, (2010), pp 117-152
Thu 08 Apr 2010, 20:06

R/BHC: Fast Bayesian Hierarchical Clustering for Microarray Data

Savage, R. S., Heller, K., Xu, Y., Ghahramani, Z., Truman, W.M., Grant, M.R., Denby, K.J. and Wild, D.L. BMC Bioinformatics, 10:242, (2009) (Highly Accessed Paper)
Thu 08 Apr 2010, 20:04

Computational approaches to the integration of gene expression, ChIP-chip and sequence data in the inference of gene regulatory networks

Cooke, E.J., Savage R.S. and Wild, D.L.  Seminars in Cell and Developmental Biology20: 863–868, (2009) (Invited Review).
Thu 08 Apr 2010, 20:04

Reconstruction and stability of secondary structure elements in the context of protein structure prediction

Podtelezhnikov, A.A. and Wild, D.L.  Biophysical Journal96:4399-4408, (2009).
Thu 08 Apr 2010, 20:03

A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series

Stegle, O., Denby, K.J., Wild, D.L., Ghahramani, Z. and Borgwardt, K.M.  Research in Computational Molecular Biology, Lecture Notes in Bioinformatics, Ed. S. Batzoglou, Springer, Berlin, 5541, 201-216, (2009).
Thu 08 Apr 2010, 20:03

Modeling and Visualizing Uncertainty in Gene Expression Clusters using Dirichlet Process Mixtures

Rasmussen, C.E., de la Cruz, B.J., Ghahramani, Z., Wild, D.L. IEEE/ACM Transactions on Computational Biology & Bioinformatics6: 615-628, (2009).
Thu 08 Apr 2010, 20:02

An approach to pathway reconstruction using whole genome metabolic models and sensitive sequence searching

Saqi, M., Dobson, R.J.B., Kraben, P., Hodgson, D.A., and Wild, D.L.  Journal of Integrative Bioinformatics, 6(1):107, (2009).
Thu 08 Apr 2010, 20:01

CRANKITE– A Fast Polypeptide Backbone Conformation Sampler

Podtelezhnikov A.A. and Wild D.L.  Source Code for Biology and Medicine, 2008, 3:12.
Thu 08 Apr 2010, 20:01

Comment on: Efficient Monte Carlo trial moves for polypeptide simulations

Podtelezhnikov A.A. and Wild D.L. Chem. Phys. 2008 129(2):027103.
Thu 08 Apr 2010, 20:00

Enhancing data integration with text analysis to find proteins implicated in plant stress response

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.

Thu 01 Apr 2010, 13:40

Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor

Mohammad T Alam, Maria E Merlo, The STREAM Consortium, David A Hodgson, Elizabeth MH Wellington, Eriko Takano, Rainer Breitling (2010). BMC Genomics 11:202.

Thu 01 Apr 2010, 13:38

The dynamic architecture of the metabolic switch in Streptomyces coelicolor

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)

Thu 01 Apr 2010, 00:11

Archaeogenetic Evidence of Ancient Nubian Barley Evolution from Six to Two-Row Indicates Local Adaptation

Palmer, S.A., Moore, J.D., Clapham, A.J., Rose, P. and Allaby, R.G. (2009) PLoS ONE 4(7): e6301.

Thu 01 Apr 2010, 00:10

The CACTA transposon Bot1 played a major role in Brassica genome divergence and gene proliferation

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. 

Thu 01 Apr 2010, 00:08

High resolution tracking of cell membrane dynamics in moving cells: An electrifying approach

R.A. Tyson, D.B.A. Epstein, K.I. Anderson, T. Bretschneider, Math. Model. Nat. Phenom., 5(1):34-55, 2010.

Wed 31 Mar 2010, 13:52

Transformation from spots to waves in a model of actin pattern formation

S. Whitelam, T. Bretschneider, N.J. Burroughs, Physical Review Letters, 102:198103, 2009.

Wed 31 Mar 2010, 13:49

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. 

Wed 31 Mar 2010, 13:44

The 3-Dimensional dynamics of actin waves, a model of cytoskeletal self-organization

T. Bretschneider, K. Anderson, M. Ecke, A. Müller-Taubenberger, B. Schroth-Diez, H.C. Ishikawa-Ankerhold, G. Gerisch, Biophys. J., 96, 2888-2900, 2009.

Wed 31 Mar 2010, 13:42

Using single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression.

M. Komorowski, B. Finkenstadt, D. A. Rand,  Biophysical Journal (to appear)
Fri 26 Mar 2010, 09:47

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

Fri 26 Mar 2010, 09:44

Bayesian inference of biochemical kinetic parameters using the linear noise approximation.

M. Komorowski, B. Finkenstadt, C. V. Harper and D. A. Rand. BMC Bioinformatics (2009) 10 343-353
Fri 26 Mar 2010, 09:43

Network control analysis for time-dependent dynamical states.

D. A. Rand. To appear in Dynamics and Games in Science, in honour of Mauricio Peixoto and David Rand. Springer 2010.
Fri 26 Mar 2010, 09:42

Pulsatile stimulation determines timing and specificity of NF-kappa B-dependent transcription.

L. Ashall, C.A. Horton, D.E. Nelson, P. Paszek, C.V. Harper, K. Sillitoe, S. Ryan, D.G. Spiller, J.F. Unitt, D.S. Broomhead, D.B. Kell, D.A. Rand, V. Sée, and M.R.H. White. Science 324 (2009) 242-246
Fri 26 Mar 2010, 09:40

Temporal clustering by affinity propagation reveals transcriptional modules in Arabidopsis thaliana

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

Wed 10 Mar 2010, 14:09

Prediction of photoperiodic regulators from quantitative gene circuit models.

Salazar, J. D, Saithong, T., Brown, P. E, Foreman, J., Locke, J. C. W., Halliday, K. J., Carré, I. A., Rand, D. A., Millar, A. J.  Cell 139: 1170-1179, 2009
Mon 08 Mar 2010, 17:07

CWRML: representing crop wild relative conservation and use data in XML

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.

Mon 08 Mar 2010, 10:54

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.

Fri 16 Jan 2009, 12:32

TreeMos: a high-throughput phylogenomic approach to find and visualise phylogenetic mosaicism.

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.

Fri 16 Jan 2009, 12:32

Stochastic niche structure and diversity maintenance in the T cell repertoire.

E.R. Stirk, C. Molina-Paris, H.A. van den Berg.  Stochastic niche structure and diversity maintenance in the T cell repertoire.  Journal of Theoretical Biology 255 (2008) 237-249.
Fri 16 Jan 2009, 12:31

The Malthusian parameter in microbial ecology and evolution: An optimal control treatment.

H. A. van den Berg, M. V. Orlov, Yu. N. Kiselev.  The Malthusian parameter in microbial ecology and evolution: An optimal control treatment.  Computational Mathematics and Modeling 19 (2008) 406-428.
Fri 16 Jan 2009, 12:31

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.

Fri 16 Jan 2009, 12:31