Open Access. Powered by Scholars. Published by Universities.®
- Keyword
Articles 1 - 3 of 3
Full-Text Articles in Computational Biology
Convolutional Neural Network-Based Gene Prediction Using Buffalograss As A Model System, Michael Morikone
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) …
Linking Taxonomic Diversity And Trophic Function: A Graph-Based Theoretical Approach, Marcella M. Jurotich, Kaitlyn Dougherty, Barbara Hayford, Sally Clark
Linking Taxonomic Diversity And Trophic Function: A Graph-Based Theoretical Approach, Marcella M. Jurotich, Kaitlyn Dougherty, Barbara Hayford, Sally Clark
Transactions of the Nebraska Academy of Sciences and Affiliated Societies
The purpose of this study is to develop a novel, visual method in analyzing complex functional trait data in freshwater ecology. We focus on macroinvertebrates in stream ecosystems under a gradient of habitat degradation and employ a combination of taxonomic and functional trait diversity analyses. Then we use graph theory to link changes in functional trait diversity to taxonomic richness and habitat degradation. We test the hypotheses that: 1) taxonomic diversity and trophic functional trait diversity both decrease with increased habitat degradation; 2) loss of taxa leads to a decrease in trophic function as visualized using a bipartite graph; and …
Bioinformatic Game Theory And Its Application To Cluster Multi-Domain Proteins, Brittney Keel
Bioinformatic Game Theory And Its Application To Cluster Multi-Domain Proteins, Brittney Keel
Department of Mathematics: Dissertations, Theses, and Student Research
The exact evolutionary history of any set of biological sequences is unknown, and all phylogenetic reconstructions are approximations. The problem becomes harder when one must consider a mix of vertical and lateral phylogenetic signals. In this dissertation we propose a game-theoretic approach to clustering biological sequences and analyzing their evolutionary histories. In this context we use the term evolution as a broad descriptor for the entire set of mechanisms driving the inherited characteristics of a population. The key assumption in our development is that evolution tries to accommodate the competing forces of selection, of which the conservation force seeks to …