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Full-Text Articles in Physical Sciences and Mathematics

Development Of An Enhanced Sampling Workflow To Accelerate Molecular Docking With Sparse Biophysical Information, Zachary Stichter May 2024

Development Of An Enhanced Sampling Workflow To Accelerate Molecular Docking With Sparse Biophysical Information, Zachary Stichter

Masters Theses & Specialist Projects

Rapid docking of flexible biological macromolecules remains a significant open challenge in protein structure determination. While rigid docking is relatively simple with toolkits such as TagDock, a key obstacle to rapid flexible docking is the complexity and roughness of the free energy surface associated with protein conformational motion (often termed the many-minima problem), meaning conventional molecular dynamics methods do not effectively sample protein conformations near the interaction complex in accessible timescales. Methods such as metadynamics and replica exchange molecular dynamics exist to ameliorate this obstacle, yet these methods use nonphysical biases or random swaps to enhance sampling. In contrast, high …


Teloportwrapper: A New Tool For Understanding The Dynamic World Of Fungal Telomere Ends, Trey Stansfield Jan 2023

Teloportwrapper: A New Tool For Understanding The Dynamic World Of Fungal Telomere Ends, Trey Stansfield

Mahurin Honors College Capstone Experience/Thesis Projects

Telomeres are repetitive DNA sequence motifs found at eukaryote chromosome ends. Telomeres help protect chromosome ends from DNA damage and promote chromosome stability. Chromosomes play important roles in aging, mutation, and cancer. Eukaryotic pathogens also use telomeres to mutate and manage virulence genes. In response to chromosome end breakage newly formed telomeres, called de novo telomeres, are formed to recreate the lost telomere and sub-telomeric regions.

Magnaporthe oryzae is a fungal pathogen which causes wheat blast, a deadly plant disease in wheat. Magnaporthe oryzae is also known for its highly variable sub-regions which show high amounts of induced variability due …


Inflammatory Bowel Disease Diagnosis Using Metagenomic Classification, Michael Riggle Apr 2020

Inflammatory Bowel Disease Diagnosis Using Metagenomic Classification, Michael Riggle

Masters Theses & Specialist Projects

Inflammatory bowel disease (IBD) is a set of disorders that involve chronic inflammation of digestive tracts, e.g., Crohn's disease (CD) and ulcerative colitis (UC). Millions of people around the world have inflammatory bowel disease. However, it is still difficult to treat IBD due to its unknown cause. In fact, accurately diagnosing inflammatory bowel disease (IBD) can be very challenging too since some of IBD symptoms can mimic those of other conditions. In this work, we apply classification methods to help improve the success rate of diagnosis. We study four formulations of IBD classification: i) IBD and non-IBD (binary classification), ii) …


A Proposed Frequency-Based Feature Selection Method For Cancer Classification, Yi Pan Apr 2017

A Proposed Frequency-Based Feature Selection Method For Cancer Classification, Yi Pan

Masters Theses & Specialist Projects

Feature selection method is becoming an essential procedure in data preprocessing step. The feature selection problem can affect the efficiency and accuracy of classification models. Therefore, it also relates to whether a classification model can have a reliable performance. In this study, we compared an original feature selection method and a proposed frequency-based feature selection method with four classification models and three filter-based ranking techniques using a cancer dataset. The proposed method was implemented in WEKA which is an open source software. The performance is evaluated by two evaluation methods: Recall and Receiver Operating Characteristic (ROC). Finally, we found the …


Using R, Matt Bogard Jan 2010

Using R, Matt Bogard

Economics Faculty Publications

R is a statistical programming language with a command line interface that is becoming more and more popular every day. I have used R for data visualization, data mining/machine learning, as well as social network analysis. Initially embraced largely in academia, R is becoming the software of choice in various corporate settings.