Computational Biology Commons^™

Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone

Complex Biosystems PhD Program: Dissertations

The task of gene prediction has been largely stagnant in algorithmic improvements compared to when algorithms were first developed for predicting genes thirty years ago. Rather than iteratively improving the underlying algorithms in gene prediction tools by utilizing better performing models, most current approaches update existing tools through incorporating increasing amounts of extrinsic data to improve gene prediction performance. The traditional method of predicting genes is done using Hidden Markov Models (HMMs). These HMMs are constrained by having strict assumptions made about the independence of genes that do not always hold true. To address this, a Convolutional Neural Network (CNN) …

Comparative Analyses Of De Novo Transcriptome Assembly Pipelines For Diploid Wheat, Natasha Pavlovikj

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Gene expression and transcriptome analysis are currently one of the main focuses of research for a great number of scientists. However, the assembly of raw sequence data to obtain a draft transcriptome of an organism is a complex multi-stage process usually composed of pre-processing, assembling, and post-processing. Each of these stages includes multiple steps such as data cleaning, error correction and assembly validation. Different combinations of steps, as well as different computational methods for the same step, generate transcriptome assemblies with different accuracy. Thus, using a combination that generates more accurate assemblies is crucial for any novel biological discoveries. Implementing …

Polerovirus Genomic Variation And Mechanisms Of Silencing Suppression By P0 Protein, Natalie Holste

School of Biological Sciences: Dissertations, Theses, and Student Research

The family Luteoviridae consists of three genera: Luteovirus, Enamovirus, and Polerovirus. The genus Polerovirus contains 32 virus species. All are transmitted by aphids and can infect a wide variety of crops from cereals and wheat to cucurbits and peppers. However, little is known about how this wide range of hosts and vectors developed. In poleroviruses, aphid transmission and virion formation is mediated by the coat protein read-through domain (CPRT) while silencing suppression and phloem limitation is mediated by Protein 0 (P0)—a protein unique to poleroviruses. P0 gives poleroviruses a great advantage amongst plant viruses and diversifies polerovirus species, but the …

Copy Number Variation In The Porcine Genome Detected From Whole-Genome Sequence, Rebecca Anderson

Honors Theses

Copy number variations (CNVs) are large insertions, deletions, and duplications in the genome that vary between individuals in a species. These variations are known to impact a broad range of phenotypes from molecular-level traits to higher-order clinical phenotypes. CNVs have been linked to complex traits in humans such as autism, attention deficit hyperactivity disorder, nervous system disorders, and early-onset extreme obesity. In this study, whole-genome sequence was obtained from 72 founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC) in Clay Center, Nebraska. This included 24 boars (12 Duroc and 12 Landrace) and …

Classification Of Genomic Sequences By Latent Semantic Analysis, Samuel F. Way

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Evolutionary distance measures provide a means of identifying and organizing related organisms by comparing their genomic sequences. As such, techniques that quantify the level of similarity between DNA sequences are essential in our efforts to decipher the genetic code in which they are written.

Traditional methods for estimating the evolutionary distance separating two genomic sequences often require that the sequences first be aligned before they are compared. Unfortunately, this preliminary step imposes great computational burden, making this class of techniques impractical for applications involving a large number of sequences. Instead, we desire new methods for differentiating genomic sequences that eliminate …