Search Constraints

Start Over
Filtering by: Creator Churchill, David J. Remove constraint Creator: Churchill, David J. Degree Field Computer Science Remove constraint Degree Field: Computer Science

Search Results

  • Position-Dependent Codon Usage Bias in the Human Transcriptome

    Creator:
    Subramanian, Kaavya
    Abstract:
    All life depends on the reliable translation of RNA to protein according to complex interactions between translation machinery and RNA sequence features. While ribosomal occupancy and codon frequencies vary across coding regions, well-established metrics for computing coding potential of RNA do not capture such positional dependence. Here, we investigate position-dependent...
    Resource Type:
    Honors College Thesis
    Full Text:
    :_____________________________________________________ David Hendrix All life depends on the reliable translation of RNA to protein according

  • Computational Approaches for RNA Structure Prediction with Dynamic Programming and Deep Neural Networks

    Creator:
    Deng, Dezhong
    Abstract:
    Our goal is to build a system to model the RNA sequences that reveals their structural information by using efficient dynamic programming algorithms and deep learning approaches. We aim to 1) achieve linear-time for RNA secondary structure prediction based on existing minimum free energy models; 2) utilize deep neural networks...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: David A. Hendrix Our goal is to build a system to model the RNA sequences that reveals

  • New Strategies to Develop Hidden Markov Models Combining KEGG and Pfam

    Creator:
    Gupta, Sonica
    Abstract:
    Profile Hidden Markov Models utilize the information stored in a multiple sequence alignment such as its residues and conserved regions to assign probabilities at each column. This indicates areas in the sequences where similar functionality is observed. These probability weights are then combined to assign a sequence score, which is...
    Resource Type:
    Honors College Thesis
    Full Text:
    . Abstract approved:_____________________________________________________ Maude David Profile

  • Determining free energies of hard sphere fluids via Monte Carlo simulation

    Creator:
    Valeskea, Austin
    Abstract:
    Free energy is a fundamental property of a thermodynamic system, from which pressure, entropy, and other interesting properties can be derived. It is useful, then, to be able to accurately compute the free energy at various densities and temperatures in a way that can serve as the basis for further...
    Resource Type:
    Honors College Thesis
    Full Text:
    : David Roundy, Mentor, representing Physics Henri J. F. Jansen, Committee Member, representing Physics

  • An enhanced version of Caesar supporting 45° geometries

    Creator:
    Lanfri, Ann R.
    Abstract:
    Caesar is an interactive graphic editor that is used to generate layouts for VLSI circuits. It runs on a VAX-11 /780 under the UNIX operating system with Berkeley extensions. Caesar has a unique and simple user interface. Phled is an enhanced version of Caesar that runs on a M68000-based engineering...
    Resource Type:
    Capstone Project
    Full Text:
    _ J The attached paper describes a project I completed on a graphic editor Phled45. The work was done

  • Tracing the Pacific Islander Diaspora in the Pacific Northwest

    Creator:
    Yarbrough, Nicole
    Abstract:
    The Pacific Islander diaspora in the Pacific Northwest United States is a unique community characterized by diverse cultures, experiences, and motivations for migration. This study aimed to explore the narratives of individuals from different Pacific Islander backgrounds residing in Oregon, shedding light on their reasons for migration and the impact...
    Resource Type:
    Honors College Thesis
    Full Text:
    Abstract approved: _____________________________________________________ David G. Lewis The

  • Automatic Classification of Ultrasonic Harbor Porpoise Clicks in a Varying Noise Environment

    Creator:
    De Leon, Daniel
    Abstract:
    This study compares three approaches in the design of an autonomous machine listening agent that predicts harbor porpoise ultrasonic echolocation clicks in diverse noise environments. Considering the temporal variations of noisy coastal ocean soundscapes which the harbor porpoises inhabit, we propose a leave-one-day-out (LODO) cross-validation strategy in the training of...
    Resource Type:
    Masters Thesis
    Full Text:
    approved: ______________________________________________________ Patrick J. Donnelly This

  • Machine Learning Methods for the Discovery and Analysis of MicroRNAs

    Creator:
    Bell, Jimmy D.
    Abstract:
    MicroRNAs are a highly conserved class of small endogenous RNA, about ~22nt in length, involved in post-transcriptional gene silencing and have prominent roles in disease and development. Though the process of microRNA discovery was once an arduous task, the advent of high throughput sequencing technology has resulted in novel microRNAs...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ David A. Hendrix MicroRNAs are a highly conserved class of small endogenous RNA, about

  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
    Resource Type:
    Dissertation
    Full Text:
    Human and Biological Languages Abstract approved: David Hendrix and Liang Huang We explore the

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation
    Full Text:
    Machine Learning: Applications in Biology and Genomics Abstract approved: David A. Hendrix Machine