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Full-Text Articles in Molecular Biology
Human 5’-Tailed Mirtrons Are Processed By Rnasep, Mohammad Farid Zia
Human 5’-Tailed Mirtrons Are Processed By Rnasep, Mohammad Farid Zia
Dissertations
Approximately a thousand microRNAs (miRNAs) are documented from human cells. A third appear to transit non-canonical pathways that typically bypass processing by Drosha, the dedicated nuclear miRNA producing enzyme. The largest class of non-canonical miRNAs are mirtrons which eschew Drosha to mature through spliceosome activity. While mirtrons are found in several configurations, the vast majority of human mirtron species are 5’-tailed. For these mirtrons, a 3’ splice site defines the 3’ end of their hairpin precursor while a “tail” of variable length separates the 5’ base of the hairpin from the nearest splice site. How this tail is removed is …
Leveraging Chemical And Computational Biology To Probe The Cellulose Synthase Complex, B. Kirtley Amos
Leveraging Chemical And Computational Biology To Probe The Cellulose Synthase Complex, B. Kirtley Amos
Theses and Dissertations--Plant and Soil Sciences
Cellular expansion in plants is a complex process driven by the constraint of internal cellular turgor pressure by an expansible cell wall. The main structural element of the cell wall is cellulose. Cellulose is vital to plant fitness and the protein complex that creates it is an excellent target for small molecule inhibition to create herbicides. In the following thesis many small molecules (SMs) from a diverse library were screened in search of new cellulose biosynthesis inhibitors (CBI). Loss of cellular expansion was the primary phenotype used to search for putative CBIs. As such, this was approached in a forward …
Applications Of Machine Learning In Microbial Forensics, Ryan B. Ghannam
Applications Of Machine Learning In Microbial Forensics, Ryan B. Ghannam
Dissertations, Master's Theses and Master's Reports
Microbial ecosystems are complex, with hundreds of members interacting with each other and the environment. The intricate and hidden behaviors underlying these interactions make research questions challenging – but can be better understood through machine learning. However, most machine learning that is used in microbiome work is a black box form of investigation, where accurate predictions can be made, but the inner logic behind what is driving prediction is hidden behind nontransparent layers of complexity.
Accordingly, the goal of this dissertation is to provide an interpretable and in-depth machine learning approach to investigate microbial biogeography and to use micro-organisms as …