Physical Sciences and Mathematics Commons^™

Fungi Of Forests: Examining The Diversity Of Root-Associated Fungi And Their Responses To Acid Deposition, Donald Jay Nelsen

Graduate Theses and Dissertations

Global importance of forests is difficult to overestimate, given their role in oxygen production, ecological roles in nutrient cycling and supporting numerous living species, and economic value for industry and as recreational zones. Fitness of the forest-forming trees strongly depends on microbial communities associated with tree roots. In particular, fungi impact tree fitness: mycorrhizal species provide water and nutrients for the trees in exchange for C, endophytic fungi play key roles in host defense against pathogenic organisms, and saprotrophic fungi decompose dead organic matter and facilitate nutrient cycling. In addition, pathogenic fungal species strongly affect forest fitness. Despite their importance, …

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 …

An Integrated Bioinformatic/Experimental Approach For Discovering Novel Type Ii Polyketides Encoded In Actinobacterial Genomes, Wubin Gao

Chemistry and Chemical Biology ETDs

Discovery of new natural products (NPs) is critical both for diseases treatment and crops protection. Numerous NP biosynthetic gene clusters (BGCs) in sequenced microbial genomes allow identification of new NPs through genome mining. Developing an integrated bioinformatic/experimental approach for discovering novel type II polyketides (PK-IIs) facilitates investigation of this family of NPs in an efficient, systematic way. Here, we developed an approach to analyze ketosynthase α/β (KSα/β) gene sequences to predict PK-II core structures, allowing us to target novel PK-II BGCs either from isolated genomic DNA or genomes from the NCBI databank, and to isolate novel PK-IIs produced by these …

Predicting Pancreatic Cancer Using Support Vector Machine, Akshay Bodkhe

Master's Projects

This report presents an approach to predict pancreatic cancer using Support Vector Machine Classification algorithm. The research objective of this project it to predict pancreatic cancer on just genomic, just clinical and combination of genomic and clinical data. We have used real genomic data having 22,763 samples and 154 features per sample. We have also created Synthetic Clinical data having 400 samples and 7 features per sample in order to predict accuracy of just clinical data. To validate the hypothesis, we have combined synthetic clinical data with subset of features from real genomic data. In our results, we observed that …

Novel Statistical Approaches For Missing Values In Truncated High-Dimensional Metabolomics Data With A Detection Threshold., Jasmit Sureshkumar Shah

Electronic Theses and Dissertations

Despite considerable advances in high throughput technology over the last decade, new challenges have emerged related to the analysis, interpretation, and integration of high-dimensional data. The arrival of omics datasets has contributed to the rapid improvement of systems biology, which seeks the understanding of complex biological systems. Metabolomics is an emerging omics field, where mass spectrometry technologies generate high dimensional datasets. As advances in this area are progressing, the need for better analysis methods to provide correct and adequate results are required. While in other omics sectors such as genomics or proteomics there has and continues to be critical understanding …

Development And Evaluation Of Machine Learning Algorithms For Biomedical Applications, Turki Talal Turki

Dissertations

Gene network inference and drug response prediction are two important problems in computational biomedicine. The former helps scientists better understand the functional elements and regulatory circuits of cells. The latter helps a physician gain full understanding of the effective treatment on patients. Both problems have been widely studied, though current solutions are far from perfect. More research is needed to improve the accuracy of existing approaches.

This dissertation develops machine learning and data mining algorithms, and applies these algorithms to solve the two important biomedical problems. Specifically, to tackle the gene network inference problem, the dissertation proposes (i) new techniques …

Integrative Pathway Analysis Pipeline For Mirna And Mrna Data, Diana Mabel Diaz Herrera

Wayne State University Theses

The identification of pathways that are involved in a particular phenotype helps us understand the underlying biological processes. Traditional pathway analysis techniques aim to infer the impact on individual pathways using only mRNA levels. However, recent studies showed that gene expression alone is unable to capture the whole picture of biological phenomena. At the same time, MicroRNAs (miRNAs) are newly discovered gene regulators that have shown to play an important role in diagnosis, and prognosis for different types of diseases. Current pathway analysis techniques do not take miRNAs into consideration. In this project, we investigate the effect of integrating miRNA …

Metabolomic Profiling Of Chiari Malformation Type I: Comparison Of Bioinformatic Programs For Untargeted Analysis, Hunter W. Korsmo

Williams Honors College, Honors Research Projects

Chiari Malformation Type I is a neurodegenerative trait that can result from disease or from acquiring. Metabolomic analysis was done on normal pressure hydrocephalous and Chiari CSF samples using LC-MS and multiple bioinformatic programs. After analysis from multiple programs, we were able to analyze the stringency in statistical algorithms done by each program and determined qualities that are shared between programs that offer multiple details. We identified dysregulation in glucuronated metabolites in CSF of Chiari versus NPH. Using LC-MS, we established the experimental MS/MS of glucuronic acid in attempt to identify similarities in mass-to-charge features primarily identified. We could not …

Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri

Theses and Dissertations

miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif …