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Understanding Host-Microbe Interactions In Maize Kernel And Sweetpotato Leaf Metagenomic Profiles., Alison K. Adams
Understanding Host-Microbe Interactions In Maize Kernel And Sweetpotato Leaf Metagenomic Profiles., Alison K. Adams
Doctoral Dissertations
Functional and quantitative metagenomic profiling remains challenging and limits our understanding of host-microbe interactions. This body of work aims to mediate these challenges by using a novel quantitative reduced representation sequencing strategy (OmeSeq-qRRS), development of a fully automated software for quantitative metagenomic/microbiome profiling (Qmatey: quantitative metagenomic alignment and taxonomic identification using exact-matching) and implementing these tools for understanding plant-microbe-pathogen interactions in maize and sweetpotato. The next generation sequencing-based OmeSeq-qRRS leverages the strengths of shotgun whole genome sequencing and costs lower that the more affordable amplicon sequencing method. The novel FASTQ data compression/indexing and enhanced-multithreading of the MegaBLAST in Qmatey allows …
Computational Analysis Of Microbial Sequence Data Using Statistics And Machine Learning, Zhixiu Lu
Computational Analysis Of Microbial Sequence Data Using Statistics And Machine Learning, Zhixiu Lu
Doctoral Dissertations
Since the discovery of the double helix of DNA in 1953, modern molecular biology has opened the door to a better understanding of how genes control chemical processes within cells, including protein synthesis. Although we are still far from claiming a complete understanding, recent advances in sequencing technologies, increased computational capacity, and more sophisticated computational methods have allowed the development of various new applications that provide further insight into DNA sequence data and how the information they encode impacts living organisms and their environment. Sequencing data can now be used to start identifying the relationships between microorganisms, where they live, …