Biostatistics Commons^™

Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares

Biology and Medicine Through Mathematics Conference

No abstract provided.

Crosstalk Among Lncrnas, Micrornas And Mrnas In The Muscle ‘Degradome’ Of Rainbow Trout, Bam Paneru, Ali Ali, Rafet Al-Tobasei, Brett Kenney, Mohamed Salem

Faculty & Staff Scholarship

In fish, protein-coding and noncoding genes involved in muscle atrophy are not fully characterized. In this study, we characterized coding and noncoding genes involved in gonadogenesis-associated muscle atrophy, and investigated the potential functional interplay between these genes. Using RNA- Seq, we compared expression pattern of mRNAs, long noncoding RNAs (lncRNAs) and microRNAs of atrophying skeletal muscle from gravid females and control skeletal muscle from age-matched sterile individuals. A total of 852 mRNAs, 1,160 lncRNAs and 28 microRNAs were differentially expressed (DE) between the two groups. Muscle atrophy appears to be mediated by many genes encoding ubiquitin- proteasome system, autophagy related …

Genome-Wide Association Analysis With A 50k Transcribed Gene Snp-Chip Identifies Qtl Affecting Muscle Yield In Rainbow Trout, Mohamed Salem, Rafet Al-Tobasei, Ali Ali, Daniela Lourenco, Guangtu Gao, Yniv Palti, Brett Kenney, Timothy D. Leeds

Faculty & Staff Scholarship

Detection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. This study has two-fold objectives, first to develop, and validate a 50K transcribed gene SNP-chip using RNA-Seq data. To achieve this objective, two bioinformatics pipelines, GATK and SAMtools, were used to identify ∼21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs ere …

Integrated Analysis Of Lncrna And Mrna Expression In Rainbow Trout Families Showing Variation In Muscle Growth And Fillet Quality Traits, Ali Ali, Rafet Al-Tobasei, Brett Kenney, Timothy D. Leeds, Mohamed Salem

Faculty & Staff Scholarship

Muscle yield and quality traits are important for the aquaculture industry and consumers. Genetic selection for these traits is difficult because they are polygenic and result from multifactorial interactions. To study the genetic architecture of these traits, phenotypic characterization of whole body weight (WBW), muscle yield, fat content, shear force and whiteness were measured in ~500 fish representing 98 families from a growth-selected line. RNA-Seq was used to sequence the muscle transcriptome of different families exhibiting divergent phenotypes for each trait. We have identified 240 and 1,280 differentially expressed (DE) protein-coding genes and long noncoding RNAs (lncRNAs), respectively, in fish …

Adverse Event Detection By Integrating Twitter Data And Vaers, Junxiang Wang, Liang Zhao, Yanfang Ye, Yuji Zhang

Faculty & Staff Scholarship

Background: Vaccinehasbeenoneofthemostsuccessfulpublichealthinterventionstodate.However,vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving vaccines. Traditional adverse event reporting systems suffer from several crucial challenges including poor timeliness. This motivates increasing social media-based detection systems, which demonstrate successful capability to capture timely and prevalent disease information. Despite these advantages, social media-based AE detection suffers from serious challenges such as labor-intensive labeling and class imbalance of the training data.

Results: Totacklebothchallengesfromtraditionalreportingsystemsandsocialmedia,weexploittheircomplementary strength and develop a combinatorial classification approach by integrating Twitter data and the Vaccine Adverse Event Reporting System (VAERS) information aiming to identify potential AEs after …

Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang

Theses and Dissertations

Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.

With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …

Testing The Independence Hypothesis Of Accepted Mutations For Pairs Of Adjacent Amino Acids In Protein Sequences, Jyotsna Ramanan, Peter Revesz

School of Computing: Faculty Publications

Evolutionary studies usually assume that the genetic mutations are independent of each other. However, that does not imply that the observed mutations are independent of each other because it is possible that when a nucleotide is mutated, then it may be biologically beneficial if an adjacent nucleotide mutates too. With a number of decoded genes currently available in various genome libraries and online databases, it is now possible to have a large-scale computer-based study to test whether the independence assumption holds for pairs of adjacent amino acids. Hence the independence question also arises for pairs of adjacent amino acids within …

Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane

Theses

Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …

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 …

Modeling And Survival Analysis Of Breast Cancer: A Statistical, Artificial Neural Network, And Decision Tree Approach, Venkateswara Rao Mudunuru

USF Tampa Graduate Theses and Dissertations

Survival analysis today is widely implemented in the fields of medical and biological sciences, social sciences, econometrics, and engineering. The basic principle behind the survival analysis implies to a statistical approach designed to take into account the amount of time utilized for a study period, or the study of time between entry into observation and a subsequent event. The event of interest pertains to death and the analysis consists of following the subject until death. Events or outcomes are defined by a transition from one discrete state to another at an instantaneous moment in time. In the recent years, research …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Evaluation Of The Signature Molecular Descriptor With Blosum62 And An All-Atom Description For Use In Sequence Alignment Of Proteins, Lindsay M. Aichinger

Williams Honors College, Honors Research Projects

This Honors Project focused on a few aspects of this topic. The second is comparing the molecular signature kernels to three of the BLOSUM matrices (30, 62, and 90) to test the accuracy of the mathematical model. The kernel matrix was manipulated in order to improve the relationship by focusing on side groups and also by changing how the structure was represented in the matrix by increasing the initial height distance from the central atom (Height 1 and Height 2 included).

There were multiple design constraints for this project. The first was the comparison with the BLOSUM matrices (30, 62, …

Roughened Random Forests For Binary Classification, Kuangnan Xiong

Legacy Theses & Dissertations (2009 - 2024)

Binary classification plays an important role in many decision-making processes. Random forests can build a strong ensemble classifier by combining weaker classification trees that are de-correlated. The strength and correlation among individual classification trees are the key factors that contribute to the ensemble performance of random forests. We propose roughened random forests, a new set of tools which show further improvement over random forests in binary classification. Roughened random forests modify the original dataset for each classification tree and further reduce the correlation among individual classification trees. This data modification process is composed of artificially imposing missing data that are …

Analytic Programming With Fmri Data: A Quick-Start Guide For Statisticians Using R, Ani Eloyan, Shanshan Li, John Muschelli, Jim Pekar, Stewart Mostofsky, Brian S. Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project along with the relevant R code. The goal is to give tatisticians who would like to pursue research in this area a quick start for programming with fMRI data along with the available data visualization tools.

Secondary Structure Prediction Of Long Rna Sequences Based On Inversion Excursions And A Modularized Mapreduce Framework, Daniel Tesfai Yehdego

Open Access Theses & Dissertations

Ribonucleic acid (RNA) molecules and their secondary structures play important roles in many biological processes including gene expression and regulation. The genomes of many viruses are also RNA molecules. Since secondary structures are crucial for RNA functionality, computational predictions of the RNA secondary structures have been widely studied. However, the tremendous demands on computer memory and computing time for complex secondary structures limit the capability of existing thermodynamically based algorithms for structure predictions to handling only short RNA sequences with a few hundred bases. One approach to overcome this limitation is by first cutting long RNA sequences into shorter, non-overlapping …

Exploration And Comparison Of Methods For Combining Population- And Family-Based Genetic Association Using The Genetic Analysis Workshop 17 Mini-Exome, David W. Fardo, Anthony R. Druen, Jinze Liu, Lucia Mirea, Claire Infante-Rivard, Patrick Breheny

Biostatistics Faculty Publications

We examine the performance of various methods for combining family- and population-based genetic association data. Several approaches have been proposed for situations in which information is collected from both a subset of unrelated subjects and a subset of family members. Analyzing these samples separately is known to be inefficient, and it is important to determine the scenarios for which differing methods perform well. Others have investigated this question; however, no extensive simulations have been conducted, nor have these methods been applied to mini-exome-style data such as that provided by Genetic Analysis Workshop 17. We quantify the empirical power and false-positive …

Ranking Single Nucleotide Polymorphisms With Support Vector Regression In Continuous Phenotypes, Seif Shahidain

Theses

Support vector machines (SVM) have been used to improve the ranking of single nucleotide polymorphisms (SNPs) over traditional chi-square tests in disease case studies [2]. In this investigation, ranking SNPs with support vector regression (SVR) was compared to the Wald test in predicting continuous phenotypes. SVR-ranked SNPs consistently outperformed the Wald test-ranked SNPs to provide a more accurate prediction of the phenotype with fewer SNPs across several methods of prediction.

Rna Genome Annotation With A Focus On T. Brucei, Brett Bucci

Theses

The goal of this project is to identify untranslated regions (UTRs) and UTR-indicating patterns in the genome of T. brucei. T. brucei is an interesting organism, and as the cause of African sleeping sickness -- which infects 300,000-500,000 people and a significant number of cattle annually -- is currently the subject of considerable research. Using existing algorithms, several patterns have been found that may lead to more complete UTR annotations in the T. brucei genome. The most encouraging sequence is the 11-base sequence GAGGGIICG]TGGGG, which appears in five hypothetical genes near the tail. Discovery of several such sequences could guide …

Utr Prediction Programs For Trypanosoma Brucei, Maria Moutafis

Theses

In the past few years, the field of bioinformatics has seen a rapid increase in the need for use of various sequence analysis tools. As we advance in the fields of science and technology, new programs and software are constantly being developed in this field. Rapidly expanding gene sequence databases and rapidly evolving sequence analysis tools are providing researchers with ways to search for highly similar query sequences whether they are nucleotide, protein, or gene databases. This thesis will focus on sequence alignment tools, specifically concentrating on tools that help determine/predict non-coding regions of sequences also known as untranslated regions …

Network Activity Arising From Optimal Diameters Of Neuronal Processes, Juliane Gansert

Theses

Electrical coupling provides an important pathway for signal transmission between neurons. In several regions of the mammalian brain electrical synapses have been detected, and their role in the synchronization of neural networks and the generation of oscillations has been studied theoretically. Recently, it has been found that the amplitude of the postsynaptic potential is maximized for a specific diameter of the postsynaptic fiber.

In this thesis, the impact of the fiber's diameter on the success or failure of the action potential initiation and propagation is studied theoretically. Systems of two coupled neurons, as well as small networks, are investigated. The …

Comparative Analysis Of Parametric, Nonparametric And Permutation Methods For Differential Expression, Rahul Patil

Theses

DNA microarrays permit us to study the expression of thousands of genes simultaneously. They are now used in many different contexts to compare mRNA levels between two or more samples of cells. Microarray experiments typically give us expression measurements on a large number of genes. Increasing popularity of microarray technology has resulted in a number of tests being proposed to detect differentials expression.

The purpose of study is to compare the parametric, non parametric and permutation tests when applied to microarray data for differential expression analysis. t test (parametric), Mann Whitney test (nonparametric) and Significance of analysis (permutation ) test …

A Data Gathering Toolkit For Biological Information Integration, Munira Lokhandwala

Theses

SYSTERS is a biological information integration system containing protein sequences from many protein databases such as Swiss-Prot and TrEMBL and also protein sequences from complete genomes available at Ensembl, The Arabidopsis Information Resource, SGD and GeneDB. For some protein sequences their encoding nucleotide sequences can be found in their corresponding websites. However, for some protein sequences their encoding nucleotide sequences are missing.

The goal of this thesis is to. collect all nucleotide sequences for the protein sequences in SYSTERS and store them in a common database. There are two cases. The first case is that if the nucleotide sequences can …

Structure And Dynamics Of Soluble Guanylyl Cyclase, Kentaro Sugino

Theses

Soluble guanylyl cyclase (sGC) is one of the key enzymes involved in many fundamental biological processes including vasodilatation. It can be allosterically activated by synthetic compound such as YC-l. Recently, the 3D structure of adenylyl cyclase (AC), which is a homologue of sGC, was determined. Using AC as template and homology modeling, the 3D structure of sGC is predicted. Prior experimental work has suggested two binding modes of YC- 1. In the current investigation, molecular dynamics simulations (MD) were conducted to seek more detail of molecular mechanism of sGC activation.

From these MD simulations, a tentative mechanism of sGC activation …

2d Quantitative Structure Activity Relationship Modeling Of Methylphenidate Analogues Using Algorithm And Partial Least Square Regression, Noureen Wadhwaniya

Theses

Quantitative Structure-Activity Relationship (QSAR) analysis attempts to develop a predictive model of biological activity based on molecular descriptors. 2D QSAR uses descriptors, such as topological indices, that are independent of molecular conformation. A genetic algorithm - partial least squares (GA-PLS) approach was used to identify the molecular descriptors that correlate to the biological activity (binding affinity) of a set of 80 methylphenidate analogues and to construct a predictive model. The GA code was implemented using the fitness function (1-(n-1)(1-q²)/ (n - c)), where n is the number of compounds, c is the optimal number of components, and q …

Slimsvm : A Simple Implementation Of Support Vector Machine For Analysis Of Microarray Data, Avik Karmaker

Theses

Support Vector Machine (SVM) is a supervised machine learning technique being widely used in multiple areas of biological analysis including microarray data analysis. SlimSVM has been developed with the intention of replacing OSU SVM as the classification component of GenoIterSVM in order to make it independent of other SVM packages. GenolterSVM, developed by Dr. Marc Ma, is a SVM implementation with an iterative refinement algorithm for improved accuracy of classification of genotype microarray data. SlimSVM is an object-oriented, modular, and easy-to-use implementation written in C++. It supports dot (linear) and polynomial (non-linear) kernels. The program has been tested with artificial …

Singular Value Decomposition Of Analogs Of Gbr 12909, Anna Fiorentino

Theses

Analogs of GBR 12909 are drugs that could potentially be used to treat cocaine addiction. Singular Value Decomposition (SVD) is a multivariate analysis technique used to show relationships between the data and the variables associated with the data. The input data consists of the conformers of each analog (DM324, 728 conformers; TP250, 739 conformers) along with the eight torsional angles (Al, A2, B1-B6). A novel scaling technique was developed to address the problem of data circularity by subtracting the values of the torsional angles of the global energy minimum conformation from those of each conformer.

In SVD the original data …

Analysis Of Auf1 Targeted Mrna Sequences, Jiebo Lu

Theses

AUF 1, an A+U rich element (ARE) binding protein, plays an important role in mRNA decay. To identify the mRNAs that interact with AUF 1, mRNA derived from a human cardiac cDNA expression library was purified by AUF 1 affinity chromatography and cloned following RT-PCR. 261 sequences were obtained. The sequences were searched against two protein databases and four nucleic acid databases, and the sequence information and database search results were input into a local Microsoft Access database, BLAST-AUF 1, by Java applets for parsing document. Analysis of protein information by querying BLAST-AUF 1 identified 194 function-known proteins, which were …

Analysis Of Molecular Conformations Using Relative Planes, Deepa S. Pai

Theses

Ring substructures of a drug usually participate actively in binding to the receptor. It is necessary to study the spatial relationship of these molecular recognition features in order to determine the pharmacophore of the drug. This is a particularly difficult problem when the drug is a flexible molecule with many energetically accessible conformations.

In this research an innovative approach to calculate the relative displacement and orientation of every possible pair of rings in a given molecule was designed, tested, and implemented in the "Planes" program. Planes were defined from each of the ring substructures and the displacement and rotation of …

Random Search Conformational Analysis Of Piperazine And Piperadine Analogs Of Gbr12909 : Implicit Aqueous Solvation Effects, William A. Roosma

Theses

The object of this work was to study the effect of solvent on the conformational potential energy surface (PES) of GBR12909 analogs. Local minima on the PES's were found by the Random Search algorithm using the Sybyl molecular modeling package from Tripos, Inc., and an implicit solvent model. Two force-field/charge models were employed in the analysis: the Tripos force field with Gasteiger-Huckel charges and the MMFF94 force field with MMFF94 charges.

The effect of solvent on the location of minima in multi-dimensional torsional angle space was studied by comparison to the vacuum phase results. Minima were plotted in torsional angle …

An Analysis Of The Periodicity Of The Cell Cycle And Apoptotic Regulatory Proteins In Prostate Xenografts Using Anova And Cosinor Methods, Aleen Hosdaghian

Theses

Circadian rhythms have been found in both plants and animals, in normal tissues as well as in most tumors and human cancers. By following these rhythms in healthy and cancerous tissue, it has been possible to find optimal times to deliver a dose of drug, such that efficacy is maximized and toxicity to normal tissues is minimized. In this study, the periodicity of several cell cycle and apoptotic regulatory proteins were studied in two prostate cancer models against a dietary therapeutic agent, Selenium. The ALVA-3 1 (androgen-independent) and PC-3 (androgen-independent) prostate cancer cell lines were grown in vivo, as a …