Paul Joyce
University of Idaho
77 Papers
854 Citations
Paul Joyce is an academic researcher from University of Idaho. The author has contributed to research in topics: Population & Biology. The author has an hindex of 34, co-authored 77 publications. Previous affiliations of Paul Joyce include University of Utah & University of Southern California.
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Papers
Differences in the composition of vaginal microbial communities found in healthy Caucasian and black women
Xia Zhou,Celeste J. Brown,Zaid Abdo,Catherine C. Davis,Melanie A. Hansmann,Paul Joyce,James A. Foster,Larry J. Forney +7 more
TL;DR: It is postulate that because of differences in composition, not all vaginal communities are equally resilient, and that differences in the vaginal microbiota of Caucasian and black women may at least partly account for known disparities in the susceptibility of women in these racial groups to bacterial vaginosis and sexually transmitted diseases.
Performance-Based Selection of Likelihood Models for Phylogeny Estimation
TL;DR: This work develops a novel approach to model selection, which is based on the Bayesian information criterion, but incorporates relative branch-length error as a performance measure in a decision theory (DT) framework.
Model Selection in Phylogenetics
Jack Sullivan,Paul Joyce +1 more
TL;DR: Issues that render model-based approaches necessary are reviewed, nucleotide-based models that attempt to capture relevant features of evolutionary processes are briefly reviewed, and methods that have been applied to model selection in phylogenetics are reviewed: likelihood-ratio tests, AIC, BIC, and performance- based approaches.
Statistical methods for characterizing diversity of microbial communities by analysis of terminal restriction fragment length polymorphisms of 16S rRNA genes.
Zaid Abdo,Ursel M.E. Schüette,Stephen J. Bent,Christopher J. Williams,Larry J. Forney,Paul Joyce +5 more
TL;DR: Methods are introduced for the statistical analysis of T-RFLP data that include objective methods for determining a baseline so that 'true' peaks in electropherograms can be identified and their ability to recover the true microbial community structure generated under the assumptions made.
436
Assessing allelic dropout and genotype reliability using maximum likelihood.
TL;DR: A maximum-likelihood approach that minimizes errors by estimating genotype reliability and strategically directing replication at loci most likely to harbor errors is developed, and can incorporate additional error-generating processes as they become more clearly understood.
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