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Full-Text Articles in Life Sciences
Analyzing Genetic Variation Of The Tussock Cottongrass Among Ecotypes Along A Latitudinal Gradient Through Transcriptomics, Carmen Webster
Analyzing Genetic Variation Of The Tussock Cottongrass Among Ecotypes Along A Latitudinal Gradient Through Transcriptomics, Carmen Webster
Open Access Theses & Dissertations
The Arctic is seeing some of the most extreme effects of climate change that induce environmental pressures, including warmer temperatures and longer growing seasons. Due to this, taxa may need to adapt or migrate in order to survive. The long-lived tussock cottongrass, Eriophorum vaginatum, is a foundation species in the Arctic, and little is currently known about the genetic constraints that could be playing a role in how this species will respond to the changing climate. Specific gene families that play an important role in signaling genetic pathways related to plant phenology and response to environmental stress are likely to …
Statistical Analysis Of Genetic Sequence Variants In Whole Exome Sequencing Data From Patients With Prostate Cancer, Kelvin Ofori-Minta
Statistical Analysis Of Genetic Sequence Variants In Whole Exome Sequencing Data From Patients With Prostate Cancer, Kelvin Ofori-Minta
Open Access Theses & Dissertations
A single variation in the genetic sequence within the DNA of an organism could easily lead to beneficial, detrimental or neutral effects. Most often than not, these effects are detrimental than beneficial. While many biomedical and bioinformatics studies have been conducted to determine the genetic cause of prostate cancer (PrCa) which is still the second leading cause of cancer related death among men in the United States. An appreciable effort in statistical bioinformatics researches has been directed towards this aim. Through statistical analyses of a set of whole exome sequencing data from patients with PrCa obtained via The Cancer Genome …
Gene Selection And Classification In High-Throughput Biological Data With Integrated Machine Learning Algorithms And Bioinformatics Approaches, Abhijeet R Patil
Gene Selection And Classification In High-Throughput Biological Data With Integrated Machine Learning Algorithms And Bioinformatics Approaches, Abhijeet R Patil
Open Access Theses & Dissertations
With the rise of high throughput technologies in biomedical research, large volumes of expression profiling, methylation profiling, and RNA-sequencing data are being generated. These high-dimensional data have large number of features with small number of samples, a characteristic called the "curse of dimensionality." The selection of optimal features, which largely affects the performance of classification algorithms in machine learning models, has led to challenging problems in bioinformatics analyses of such high-dimensional datasets. In this work, I focus on the design of two-stage frameworks of feature selection and classification and their applications in multiple sets of colorectal cancer data. The first …