Life Sciences Commons^™

Ncrna-Protein Interaction Prediction Using Language-Based Features, Krishna Shah

University of New Orleans Theses and Dissertations

Noncoding RNAs (ncRNAs) play a significant role in several fundamental biological processes by binding to RNA-binding proteins (RBPs); hence, it is necessary to study ncRNA-protein interaction (RPI). Several classic and deep-learning machine learning models have been pro-posed to predict RPI. These models first need to collect features of RNA and protein, such as physicochemical properties, secondary and tertiary structure, et cetera, before feeding them into the model. More recently, after the advancement of high throughput sequenc-ing and the improvement in Natural Language Processing (NLP), transformer models like BERT-RBP and Evolutionary Scaling Model (ESM) can be trained to automatically extract feature …

A Transcriptomic Exploration Of Hawaiian Drosophilid Development And Evolution, Madeline M. Chenevert

University of New Orleans Theses and Dissertations

One in four known species of fruit flies inhabit the Hawaiian Islands. From a small number of colonizing flies, a wide range of species evolved, some of which managed to reverse-colonize other continental environments. In order to explore the developmental pathways, which separate the Hawaiian Drosophila proper and the Scaptomyza group that contains reverse-colonized species, the transcriptomes of two better-known species in each group, Scaptomyza anomala and Drosophila grimshawi, were analyzed to find changes in gene expression between the two groups. This study describes a novel transcriptome for S. anomala studies as well as unusual changes in gene expression …

Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra

University of New Orleans Theses and Dissertations

Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on …

Formulation Of Hybrid Knowledge-Based/Molecular Mechanics Potentials For Protein Structure Refinement And A Novel Graph Theoretical Protein Structure Comparison And Analysis Technique, Aaron Maus

University of New Orleans Theses and Dissertations

Proteins are the fundamental machinery that enables the functions of life. It is critical to understand them not just for basic biology, but also to enable medical advances. The field of protein structure prediction is concerned with developing computational techniques to predict protein structure and function from a protein’s amino acid sequence, encoded for directly in DNA, alone. Despite much progress since the first computational models in the late 1960’s, techniques for the prediction of protein structure still cannot reliably produce structures of high enough accuracy to enable desired applications such as rational drug design. Protein structure refinement is the …

Understanding The Impacts Of Current And Future Environmental Variation On Central African Amphibian Biodiversity, Courtney A. Miller

University of New Orleans Theses and Dissertations

Global climate change is projected to impact multiple levels of biodiversity by imposing strong selection pressures on existing populations, triggering shifts in species distributions, and reorganizing entire communities. The Lower Guineo-Congolian region in central Africa, a reservoir for amphibian diversity, is predicted to be severely affected by future climate change through rising temperatures and greater variability in rainfall. Geospatial modelling can be used to assess how environmental variation shapes patterns of biological variation – from the genomic to the community level – and use these associations to predict patterns of biological change across space and time. The overall goal of …

Machine Learning Based Protein Sequence To (Un)Structure Mapping And Interaction Prediction, Sumaiya Iqbal

University of New Orleans Theses and Dissertations

Proteins are the fundamental macromolecules within a cell that carry out most of the biological functions. The computational study of protein structure and its functions, using machine learning and data analytics, is elemental in advancing the life-science research due to the fast-growing biological data and the extensive complexities involved in their analyses towards discovering meaningful insights. Mapping of protein’s primary sequence is not only limited to its structure, we extend that to its disordered component known as Intrinsically Disordered Proteins or Regions in proteins (IDPs/IDRs), and hence the involved dynamics, which help us explain complex interaction within a cell that …

Dispredict: A Predictor Of Disordered Protein Using Optimized Rbf Kernel, Sumaiya Iqbal, Md Tamjidul Hoque

Computer Science Faculty Publications

Intrinsically disordered proteins or, regions perform important biological functions through their dynamic conformations during binding. Thus accurate identification of these disordered regions have significant implications in proper annotation of function, induced fold prediction and drug design to combat critical diseases. We introduce DisPredict, a disorder predictor that employs a single support vector machine with RBF kernel and novel features for reliable characterization of protein structure. DisPredict yields effective performance. In addition to 10-fold cross validation, training and testing of DisPredict was conducted with independent test datasets. The results were consistent with both the training and test error minimal. The use …

Three-Dimensional Ideal Gas Reference State Based Energy Function, Avdesh Mishra

University of New Orleans Theses and Dissertations

Energy functions are found to be a key of protein structure prediction. In this work, we propose a novel 3-dimensional energy function based on hydrophobic-hydrophilic properties of amino acid where we consider at least three different possible interaction of amino acid in a 3-dimensional sphere categorized as hydrophilic versus hydrophilic, hydrophobic versus hydrophobic and hydrophobic versus hydrophilic. Each of these interactions are governed by a 3-dimensional parameter alpha used to model the interaction and 3-dimensional parameter beta used to model weight of contribution. We use Genetic Algorithm (GA) to optimize the value of alpha, beta and Z-score. We obtain three …

Statistical And Comparative Phylogeography Of Mexican Freshwater Taxa In Extreme Aquatic Environments, Lyndon M. Coghill

University of New Orleans Theses and Dissertations

Phylogeography aims to understand the processes that underlie the distribution of genetic variation within and among closely related species. Although the means by which this goal might be achieved differ considerably from those that spawned the field some thirty years ago, the foundation and conceptual breakthroughs made by Avise are nonetheless the same and are as relevant today as they were two decades ago. Namely, patterns of neutral genetic variation among individuals carry the signature of a species’ demographic past, and the spatial and temporal environmental heterogeneity across a species’ geographic range can influence patterns of evolutionary change. Aquatic systems …

Pcaanalyser: A 2d-Image Analysis Based Module For Effective Determination Of Prostate Cancer Progression In 3d Culture, Md Tamjidul Hoque, Louisa C. E. Windus, Carrie J. Lovitt, Vicky M. Avery

Computer Science Faculty Publications

Three-dimensional (3D) in vitro cell based assays for Prostate Cancer (PCa) research are rapidly becoming the preferred alternative to that of conventional 2D monolayer cultures. 3D assays more precisely mimic the microenvironment found in vivo, and thus are ideally suited to evaluate compounds and their suitability for progression in the drug discovery pipeline. To achieve the desired high throughput needed for most screening programs, automated quantification of 3D cultures is required. Towards this end, this paper reports on the development of a prototype analysis module for an automated high-content-analysis (HCA) system, which allows for accurate and fast investigation of …

Evolution Of Nuclear Integrations Of The Mitochondrial Genome In Great Apes And Their Potential As Molecular Markers, Ivan D. Soto-Calderon

University of New Orleans Theses and Dissertations

The mitochondrial control region (MCR) has played an important role as a population genetic marker in many taxa but sequencing of complete eukaryotic genomes has revealed that nuclear integrations of mitochondrial DNA (numts) are abundant and widespread across many taxa. If left undetected, numts can inflate mitochondrial diversity and mislead interpretation of phylogenetic relationships. Comparative analyses of complete genomes in humans, orangutans and chimpanzees, and preliminary studies in gorillas have revealed high numt prevalence in great apes, but rigorous comparative analyses across taxa have been lacking.

The present study aimed to systematically compare the evolutionary dynamics of MCR numts in …

Multivariate Models And Algorithms For Systems Biology, Lipi Rani Acharya

University of New Orleans Theses and Dissertations

Rapid advances in high-throughput data acquisition technologies, such as microarraysand next-generation sequencing, have enabled the scientists to interrogate the expression levels of tens of thousands of genes simultaneously. However, challenges remain in developingeffective computational methods for analyzing data generated from such platforms. In thisdissertation, we address some of these challenges. We divide our work into two parts. Inthe first part, we present a suite of multivariate approaches for a reliable discovery of geneclusters, often interpreted as pathway components, from molecular profiling data with replicated measurements. We translate our goal into learning an optimal correlation structure from replicated complete and incomplete …

Computational Pipeline For Human Transcriptome Quantification Using Rna-Seq Data, Guorong Xu

University of New Orleans Theses and Dissertations

The main theme of this thesis research is concerned with developing a computational pipeline for processing Next-generation RNA sequencing (RNA-seq) data. RNA-seq experiments generate tens of millions of short reads for each DNA/RNA sample. The alignment of a large volume of short reads to a reference genome is a key step in NGS data analysis. Although storing alignment information in the Sequence Alignment/Map (SAM) or Binary SAM (BAM) format is now standard, biomedical researchers still have difficulty accessing useful information. In order to assist biomedical researchers to conveniently access essential information from NGS data files in SAM/BAM format, we have …