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Full-Text Articles in Physical Sciences and Mathematics

Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr. Aug 2016

Bayesian Networks To Assess The Newborn Stool Microbiome, William E. Bennett Jr.

McKelvey School of Engineering Theses & Dissertations

In human stool, a large population of bacterial genes and transcripts from hundreds of genera coexist with host genes and transcripts. Assessments of the metagenome and transcriptome are particularly challenging, since there is a great deal of sequence overlap among related species and related genes. We sequenced the total RNA content from stool samples in a neonate using previously-described methods. We then performed stepwise alignment of different populations of RNA sequence reads to different indices, including ribosomal databases, the human genome, and all sequenced bacterial genomes. Each pool of RNA at each alignment step was subjected to compression to assess …


Identification Of Errors In Cotton Fiber Data Sets Using Bayesian Networks, G F. Sassenrath, J. E. Boggess, Xintong Bi, H. C. Pringle Apr 2004

Identification Of Errors In Cotton Fiber Data Sets Using Bayesian Networks, G F. Sassenrath, J. E. Boggess, Xintong Bi, H. C. Pringle

Conference on Applied Statistics in Agriculture

Cotton fiber is graded on a series of parameters based on physiological factors (strength, length, and thickness), lint color, and presence of non-lint matter such as leaves, stems or other foreign materials. Cotton lint is graded by the USDA-AMS after harvest and ginning, and the grade determines the price of the lint. Given the importance of cotton fiber quality to the value of the crop, the spatial variability of cotton fiber properties is of particular interest to researchers and producers in developing management scenarios for optimal profitability. Previous research studies have relied on hand-harvesting the cotton at intervals throughout the …