Experts and Doctors on bayes theorem in Brisbane, Queensland, Australia

Summary

Locale: Brisbane, Queensland, Australia
Topic: bayes theorem

Top Publications

  1. Assareh H, Smith I, Mengersen K. Bayesian change point detection in monitoring cardiac surgery outcomes. Qual Manag Health Care. 2011;20:207-22 pubmed publisher
    ..We then identify the time of changes in prior signals obtained from charts. Study of the known potential causes of changes in the outcomes reveals that estimated change points and shifts in the known causes are coincident. ..
  2. Drovandi C, Pettitt A. Bayesian experimental design for models with intractable likelihoods. Biometrics. 2013;69:937-48 pubmed publisher
    ..The macroparasite example involves a multivariate process and we assess the loss of information from not observing all variables. ..
  3. Turner L, Barnett A, Connell D, Tong S. Ambient temperature and cardiorespiratory morbidity: a systematic review and meta-analysis. Epidemiology. 2012;23:594-606 pubmed publisher
    ..The effects of temperature on cardiorespiratory morbidity seemed to be smaller and more variable than previous findings related to mortality. ..
  4. Reid H, Haque U, Clements A, Tatem A, Vallely A, Ahmed S, et al. Mapping malaria risk in Bangladesh using Bayesian geostatistical models. Am J Trop Med Hyg. 2010;83:861-7 pubmed publisher
    ..Importantly, malaria risk was found to be highly varied across the endemic regions, necessitating the targeting of resources to reduce the burden in these areas. ..
  5. Li J, Udy A, Kirkpatrick C, Lipman J, Roberts J. Improving vancomycin prescription in critical illness through a drug use evaluation process: a weight-based dosing intervention study. Int J Antimicrob Agents. 2012;39:69-72 pubmed publisher
    ..However, subtherapeutic exposures were still prevalent and may warrant more vigilant promotion of the dosing protocol to ensure that recommended vancomycin doses are used in this population. ..
  6. Choy S, O Leary R, Mengersen K. Elicitation by design in ecology: using expert opinion to inform priors for Bayesian statistical models. Ecology. 2009;90:265-77 pubmed
    ..Analysis of these examples reveals several recurring important issues affecting practical design of elicitation in ecological problems. ..
  7. Avent M, Vaska V, Rogers B, Cheng A, van Hal S, Holmes N, et al. Vancomycin therapeutics and monitoring: a contemporary approach. Intern Med J. 2013;43:110-9 pubmed publisher
    ..We recommend the use of these programs providing there is appropriate expertise available to make appropriate recommendations. ..
  8. Johnson S, Mengersen K. Integrated Bayesian network framework for modeling complex ecological issues. Integr Environ Assess Manag. 2012;8:480-90 pubmed publisher
  9. Mehdi A, Sehgal M, Kobe B, Bailey T, Boden M. A probabilistic model of nuclear import of proteins. Bioinformatics. 2011;27:1239-46 pubmed publisher
    ..84 and 0.80, respectively). The model also predicts the sequence position of a nuclear localization signal and whether it interacts with importin-?. http://pprowler.itee.uq.edu.au/NucImport ..

More Information

Publications30

  1. Raso G, Vounatsou P, McManus D, N Goran E, Utzinger J. A Bayesian approach to estimate the age-specific prevalence of Schistosoma mansoni and implications for schistosomiasis control. Int J Parasitol. 2007;37:1491-500 pubmed
    ..The model presented here can be utilized to estimate S. mansoni community infection prevalences, which in turn helps in the strategic planning of schistosomiasis control. ..
  2. Rakhit D, Downey M, Jeffries L, Moir S, Prins J, Marwick T. Screening for coronary artery disease in patients with diabetes: a Bayesian strategy of clinical risk evaluation and exercise echocardiography. Am Heart J. 2005;150:1074-80 pubmed
    ..03) and DCRS (12% vs 2%, P = .01). Combination of the UKPDS or DCRS with ExE may optimize detection of coronary artery disease and cardiac events in asymptomatic patients, while minimizing the numbers of ExE and false-positive rate. ..
  3. Drovandi C, Pettitt A. Estimation of parameters for macroparasite population evolution using approximate bayesian computation. Biometrics. 2011;67:225-33 pubmed publisher
    ..The fitted model explains the observed extra-binomial variation in terms of a zero-one immunity variable, which has a short-lived presence in the host...
  4. Raso G, Vounatsou P, McManus D, Utzinger J. Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist. Geospat Health. 2007;2:85-96 pubmed
    ..We argue that in settings where S. mansoni and hookworm co-exist and control efforts are under way, there is a need for both mono- and co-infection risk maps to enhance the cost-effectiveness of control programmes...
  5. Bigdeli T, Ripke S, Peterson R, Trzaskowski M, Bacanu S, Abdellaoui A, et al. Genetic effects influencing risk for major depressive disorder in China and Europe. Transl Psychiatry. 2017;7:e1074 pubmed publisher
    ..Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies...
  6. Meadows J, Cemal I, Karaca O, Gootwine E, Kijas J. Five ovine mitochondrial lineages identified from sheep breeds of the near East. Genetics. 2007;175:1371-9 pubmed
  7. Baade P, Dasgupta P, Aitken J, Turrell G. Geographic remoteness, area-level socioeconomic disadvantage and inequalities in colorectal cancer survival in Queensland: a multilevel analysis. BMC Cancer. 2013;13:493 pubmed publisher
    ..Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC. ..
  8. de Villemereuil P, Wells J, Edwards R, Blomberg S. Bayesian models for comparative analysis integrating phylogenetic uncertainty. BMC Evol Biol. 2012;12:102 pubmed publisher
    ..Code for all models is provided in the BUGS model description language. ..
  9. Cridland J, Curley E, Wykes M, Schroder K, Sweet M, Roberts T, et al. The mammalian PYHIN gene family: phylogeny, evolution and expression. BMC Evol Biol. 2012;12:140 pubmed
    ..Non-genomic DNA can indicate infection, or a mutagenic threat. We hypothesise that defence of the genome against endogenous retroelements has been an additional evolutionary driver for PYHIN proteins. ..
  10. Chen G, Lee S, Montgomery G, Wray N, Visscher P, Gearry R, et al. Performance of risk prediction for inflammatory bowel disease based on genotyping platform and genomic risk score method. BMC Med Genet. 2017;18:94 pubmed publisher
    ..Although a quantitative assessment of IBD risk for an individual is not currently possible, we show sufficient power of genomic risk scores to stratify IBD risk among individuals at diagnosis. ..
  11. Cespedes M, Fripp J, McGree J, Drovandi C, Mengersen K, Doecke J. Comparisons of neurodegeneration over time between healthy ageing and Alzheimer's disease cohorts via Bayesian inference. BMJ Open. 2017;7:e012174 pubmed publisher
    ..A Bayesian framework for LME models in AD is introduced in this paper to provide additional insight often not found in current LME volumetric analyses...
  12. Lin Y, Edwards R, Kondo T, Semple T, Cook L. Species delimitation in asexual insects of economic importance: The case of black scale (Parasaissetia nigra), a cosmopolitan parthenogenetic pest scale insect. PLoS ONE. 2017;12:e0175889 pubmed publisher
    ..Introduction of additional lineages could expand the geographic extent of damage by the pest in some countries. ..
  13. Hu W, O Leary R, Mengersen K, Low Choy S. Bayesian classification and regression trees for predicting incidence of cryptosporidiosis. PLoS ONE. 2011;6:e23903 pubmed publisher
    ..In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis infection in Queensland, Australia...
  14. Thompson B, Greenblatt M, Vallée M, Herkert J, Tessereau C, Young E, et al. Calibration of multiple in silico tools for predicting pathogenicity of mismatch repair gene missense substitutions. Hum Mutat. 2013;34:255-65 pubmed publisher
    ..93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions. ..
  15. Mar J, Harlow T, Ragan M. Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation. BMC Evol Biol. 2005;5:8 pubmed
  16. Chan C, Beiko R, Ragan M. Detecting recombination in evolving nucleotide sequences. BMC Bioinformatics. 2006;7:412 pubmed
  17. Schmidt S, Walter G. Young clades in an old family: major evolutionary transitions and diversification of the eucalypt-feeding pergid sawflies in Australia (Insecta, Hymenoptera, Pergidae). Mol Phylogenet Evol. 2014;74:111-21 pubmed publisher
  18. Cristino A, Nunes F, Barchuk A, Aguiar Coelho V, Simões Z, Bitondi M. Organization, evolution and transcriptional profile of hexamerin genes of the parasitic wasp Nasonia vitripennis (Hymenoptera: Pteromalidae). Insect Mol Biol. 2010;19 Suppl 1:137-46 pubmed publisher
    ..Temporal and spatial transcriptional profiles of N. vitripennis hexamerins suggest that they have physiological functions other than metamorphosis, which are arguably coupled with its lifestyle. ..
  19. Keith J. Sequence segmentation. Methods Mol Biol. 2008;452:207-29 pubmed publisher
    ..math.sci.qut.edu.au/~keith/) . ..
  20. Lloyd Jones L, Robinson M, Moser G, Zeng J, Beleza S, Barsh G, et al. Inference on the Genetic Basis of Eye and Skin Color in an Admixed Population via Bayesian Linear Mixed Models. Genetics. 2017;206:1113-1126 pubmed publisher
    ..The Bayesian LMMs provide evidence for two new pigmentation loci: one for eye color (AHRR) and one for skin color (DDB1). ..
  21. Beiko R, Harlow T, Ragan M. Highways of gene sharing in prokaryotes. Proc Natl Acad Sci U S A. 2005;102:14332-7 pubmed
    ..The inferred relationships suggest a pattern of inheritance that is largely vertical, but with notable exceptions among closely related taxa, and among distantly related organisms that live in similar environments. ..