Bioinformatics Commons^™

Uncovering Novel Small Regulatory Rna In Protostome, Sweta Khanal

Dissertations

Small RNAs play pivotal roles in post-transcriptional gene regulation across diverse phylum of protostomes. In this study, we investigate the functional significance of atypical miRNAs, mirtron miR-1017 in Drosophila. Through ectopic expression in neuronal cells, we demonstrate that miR-1017 extends lifespan by targeting its host transcript, acetylcholine receptor Dα2, and influencing its splicing. This novel trans-regulatory function suggests a mechanism for mirtron evolution, highlighting the interplay between splicing and post-transcriptional regulation. Additionally, we profile small RNA populations in the polychaete developmental model Capitella teleta, shedding light on the small RNA landscape in annelid worms. Our analysis reveals a rich …

Model-Based Deep Autoencoders For Clustering Single-Cell Rna Sequencing Data With Side Information, Xiang Lin

Dissertations

Clustering analysis has been conducted extensively in single-cell RNA sequencing (scRNA-seq) studies. scRNA-seq can profile tens of thousands of genes' activities within a single cell. Thousands or tens of thousands of cells can be captured simultaneously in a typical scRNA-seq experiment. Biologists would like to cluster these cells for exploring and elucidating cell types or subtypes. Numerous methods have been designed for clustering scRNA-seq data. Yet, single-cell technologies develop so fast in the past few years that those existing methods do not catch up with these rapid changes and fail to fully fulfil their potential. For instance, besides profiling transcription …

A Genomic Investigation Of Divergence Between Tuna Species, Pavel V. Dimens

Dissertations

Effective management and conservation of marine pelagic fishes is heavily dependent on a robust understanding of their population structure, their evolutionary history, and the delineation of appropriate management units. The Yellowfin tuna (Thunnus albacares) and the Blackfin tuna (Thunnus atlanticus) are two exploited epipelagic marine species with overlapping ranges in the tropical and sub-tropical Atlantic Ocean. This work analyzed genome-wide genetic variation of both species in the Atlantic basin to investigate the occurrence of population subdivision and adaptive variation. A de novo assembly of the Blackfin tuna genome was generated using Illumina paired-end sequencing data and …

Characterizing Endogenous Dicer Products To Unravel Novel Rnai Biogenesis Pathways, Jacob Oche Peter

Dissertations

ABSTRACT

RNA interference (RNAi) is a pervasive gene regulatory mechanism in eukaryotes based on the action of multiple classes of small RNA (sRNA). Exploiting RNAi pathways in non-model systems have great potential for creating potent RNAi technologies. Here, we accessed RNAi-mediated control of gene expression in the two-spotted spider mite, Tetranychus urticae (T. urticae) using engineered dsRNA designed to modulate the host RNAi pathway and increase RNAi efficacy. Analysis of Dicer (Dcr) generated fragments revealed how exogenous RNAs access the host RNAi pathway in this animal, opening avenues for designing RNAi technology for their control. Further, some organisms …

Human 5’-Tailed Mirtrons Are Processed By Rnasep, Mohammad Farid Zia

Dissertations

Approximately a thousand microRNAs (miRNAs) are documented from human cells. A third appear to transit non-canonical pathways that typically bypass processing by Drosha, the dedicated nuclear miRNA producing enzyme. The largest class of non-canonical miRNAs are mirtrons which eschew Drosha to mature through spliceosome activity. While mirtrons are found in several configurations, the vast majority of human mirtron species are 5’-tailed. For these mirtrons, a 3’ splice site defines the 3’ end of their hairpin precursor while a “tail” of variable length separates the 5’ base of the hairpin from the nearest splice site. How this tail is removed is …

Methods For Extending Biomedical Reference Ontologies And Interface Terminologies For Ehrr Text Annotation, Vipina Kuttichi Keloth

Dissertations

Biomedical ontologies and terminologies are a cornerstone in various electronic health record systems (EHRs) for encoding information related to diseases, diagnoses, treatments, etc. Ontologies in general represent entities (concepts) and events along with all interdependent properties and relationships in an efficient way to facilitate easy access, retrieval and sharing. With the landscape of medicine rapidly changing, biomedical ontologies and terminologies need to rapidly evolve to support interoperability, medical coding, record keeping, and healthcare activities in general, and to facilitate interdisciplinary research. Extending ontologies by identifying new and missing concepts plays a vital role in the maintenance of ontologies to keep …

Enrichment Of Ontologies Using Machine Learning And Summarization, Hao Liu

Dissertations

Biomedical ontologies are structured knowledge systems in biomedicine. They play a major role in enabling precise communications in support of healthcare applications, e.g., Electronic Healthcare Records (EHR) systems. Biomedical ontologies are used in many different contexts to facilitate information and knowledge management. The most widely used clinical ontology is the SNOMED CT. Placing a new concept into its proper position in an ontology is a fundamental task in its lifecycle of curation and enrichment.

A large biomedical ontology, which typically consists of many tens of thousands of concepts and relationships, can be viewed as a complex network with concepts as …

Cancer Risk Prediction With Whole Exome Sequencing And Machine Learning, Abdulrhman Fahad M Aljouie

Dissertations

Accurate cancer risk and survival time prediction are important problems in personalized medicine, where disease diagnosis and prognosis are tuned to individuals based on their genetic material. Cancer risk prediction provides an informed decision about making regular screening that helps to detect disease at the early stage and therefore increases the probability of successful treatments. Cancer risk prediction is a challenging problem. Lifestyle, environment, family history, and genetic predisposition are some factors that influence the disease onset. Cancer risk prediction based on predisposing genetic variants has been studied extensively. Most studies have examined the predictive ability of variants in known …

The Antimicrobial Activity And Cellular Targets Of Plant Derived Aldehydes And Degradable Pro-Antimicrobial Networks In Pseudomonas Aeruginosa, Yetunde Adewunmi

Dissertations

Essential oils (EOs) are plant-derived products that have been long exploited for their antimicrobial activities in medicine, agriculture, and food preservation. EOs represent a promising alternative to conventional antibiotics due to the broad-range antimicrobial activity, low toxicity to human commensal bacteria, and the capacity to kill microorganisms without promoting resistance. Despite the progress in the understanding of the biological activity of EOs, many aspects of their mode of action remain inconclusive. The overarching aim of this work was to address these gaps by studying molecular interactions between antimicrobial plant aldehydes and the opportunistic human pathogen Pseudomonas aeruginosa. We initiated …

Model-Based Deep Autoencoders For Characterizing Discrete Data With Application To Genomic Data Analysis, Tian Tian

Dissertations

Deep learning techniques have achieved tremendous successes in a wide range of real applications in recent years. For dimension reduction, deep neural networks (DNNs) provide a natural choice to parameterize a non-linear transforming function that maps the original high dimensional data to a lower dimensional latent space. Autoencoder is a kind of DNNs used to learn efficient feature representation in an unsupervised manner. Deep autoencoder has been widely explored and applied to analysis of continuous data, while it is understudied for characterizing discrete data. This dissertation focuses on developing model-based deep autoencoders for modeling discrete data. A motivating example of …

The Influence Of Conservation Tillage And Conventional Tillage On Soil Bacterial Diversity In Southern Illinois, Nasser Syed

Dissertations

Agriculture in the Midwest United States (Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio, and Wisconsin) is a critically important component of the United States economy and also for world exports of food grain. This is well reflected in the 2012 Census of Agriculture which showed that these states had a market value of crop and livestock products sold in excess of $80,000,000,000 (USDA, 2012). Within the U.S. the three Midwest states, Illinois, Iowa, and Minnesota are ranked 2nd, 3rd, and 4th for the economic value of crops sold. This economic value of agriculture in the Midwest encompasses not only corn, soybeans, …

Development, Evaluation, And Application Of A Novel Error Correction Method For Next Generation Sequencing Data, Isaac Akogwu

Dissertations

Tremendous evolvement in sequencing technologies and the vast availability of data due to decreasing cost of Next-Generation-Sequencing (NGS) has availed scientists the opportunity to address a wide variety of evolutionary and biological issues. NGS uses massively parallel technology to accelerate the process at the expense of accuracy and read length in comparison to earlier Sanger methods. Therefore, computational limitations exist in how much analysis and information can be gleaned from the data without performing some form of error correction.

Error correction process is laborious and consumes a lot of computational resources. Despite the existence of many NGS data error correction …

Biophysical Studies Of Hairpin Polyamides With Broad-Spectrum Activity Against High-Risk Human Papillomaviruses, Carlos H. Castaneda

Dissertations

Human papillomavirus is a small dsDNA virus that infects mucosal and cutaneous epithelial tissues. Persistent infection with high-risk HPV is the main etiological agent in the development of cervical cancer worldwide. Although prophylactic vaccines against HPV are available, these preventative measures are type-specific and are ineffective against existing infections. Thus, there is a pressing need for antiviral drugs with a broad-spectrum activity against HPV to eradicate existing infections, no matter the subtype.

Our group and collaborators have synthesized an extensive library of novel N-methylpyrrole/N-methylimidazole (Py/Im) hairpin polyamides (PAs) with broad-spectrum activities against three prevalent oncogenic-HPV types (HPV16, …

Knowledge-Based Analysis Of Genomic Expression Data By Using Different Machine Learning Algorithms For The Purpose Of Diagnostic, Prognostic Or Therapeutic Application, Venkata Jagan Mohan Thodima

Dissertations

With more and more biological information generated, the most pressing task of bioinformatics has become to analyze and interpret various types of data, including nucleotide and amino acid sequences, protein structures, gene expression profiling and so on. In this dissertation, we apply the data mining techniques of feature generation, feature selection, and feature integration with learning algorithms to tackle the problems of disease phenotype classification, clinical outcome and patient survival prediction from gene expression profiles.

We analyzed the effect of batch noise in microarray data on the performance of classification. Batchmatch, a batch adjusting algorithm based on double scaling method …