Physical Sciences and Mathematics Commons^™

40th Annual Wku Student Research Conference, Student Research Council, Western Kentucky University

Student Research Conference Select Presentations

No abstract provided.

Estimating The Proportion Of Equivalently Expressed Genes In Microarray Data Based On Transformed Test Statistics, Shuo Jiao, Shunpu Zhang

Shuo Jiao

In microarray data analysis, false discovery rate (FDR) is now widely accepted as the control criterion to account for multiple hypothesis testing. The proportion of equivalently expressed genes (π0) is a key component to be estimated in the estimation of FDR. Some commonly used π0 estimators (BUM, SPLOSH, QVALUE, and LBE ) are all based on p-values, and they are essentially upper bounds of π0. The simulations we carried out show that these four methods significantly overestimate the true π0 when differentially expressed genes and equivalently expressed genes are not well separated. To solve this problem, we first introduce a …

Culturally-Adapted And Audio-Technology Assisted Hiv/Aids Awareness And Education Program In Rural Nigeria: A Cohort Study, Ighovwerha Ofotokun, Jose Nilo G. Binongo, Eli S. Rosenberg, Michael Kane, Rick Ifland, Jeffrey L. Lennox, Kirk A. Easley

Faculty Articles

Background: HIV-awareness programs tailored toward the needs of rural communities are needed. We sought to quantify change in HIV knowledge in three rural Nigerian villages following an integrated culturally adapted and technology assisted educational intervention.

Methods: A prospective 14-week cohort study was designed to compare short-term changes in HIV knowledge between seminar-based education program and a novel program, which capitalized on the rural culture of small-group oral learning and was delivered by portable digital-audio technology.

Results: Participants were mostly Moslem (99%), male (53.5%), with no formal education (55%). Baseline HIV knowledge was low (< 80% correct answers for 9 of the 10 questions). Knowledge gain was higher (p < 0.0001 for 8 of 10 questions) in the integrated culturally adapted and technology-facilitated (n = 511) compared with the seminar-based (n = 474) program.

Conclusions: Baseline HIV-awareness was low. Culturally …

Segmentation Of Thermographic Images Of Hands Using A Genetic Algorithm, Payel Ghosh, Judith Gold, Melanie Mitchell

Computer Science Faculty Publications and Presentations

This paper presents a new technique for segmenting thermographic images using a genetic algorithm (GA). The individuals of the GA also known as chromosomes consist of a sequence of parameters of a level set function. Each chromosome represents a unique segmenting contour. An initial population of segmenting contours is generated based on the learned variation of the level set parameters from training images. Each segmenting contour (an individual) is evaluated for its fitness based on the texture of the region it encloses. The fittest individuals are allowed to propagate to future generations of the GA run using selection, crossover and …

Manifest Greatness The Final Original Version By Emmanuel Mario B Santos Aka Marc Guerrero, Emmanuel Mario B. Santos Aka Marc Guerrero

Emmanuel Mario B Santos aka Marc Guerrero

MANIFEST GREATNESS vf24jan2010 WE COME TOGETHER THERE OUGHT TO BE NO POOR WE TAKE CHARGE.

Ssrn As An Initial Revolution In Academic Knowledge Aggregation And Dissemination, David Bray, Sascha Vitzthum, Benn Konsynski

Sascha Vitzthum

Within this paper we consider our results of using the Social Science Research Network (SSRN) over a period of 18 months to distribute our working papers to the research community. Our experiences have been quite positive, with SSRN serving as a platform both to inform our colleagues about our research as well as inform us about related research (through email and telephoned conversations of colleagues who discovered our paper on SSRN). We then discuss potential future directions for SSRN to consider, and how SSRN might well represent an initial revolution in 21st century academic knowledge aggregation and dissemination. Our paper …

Domains Of Water Molecules Provide Mechanisms Of Potentization In Homeopathy, George Czerlinski, Tjalling Ypma

Mathematics Faculty Publications

In homeopathy, high potentization means such high dilution that there is no longer even one molecule of the original active agent per gram of the mixture. Nevertheless such high dilutions apparently remain effective. We develop a possible mechanism for homeopathic potentization to explain this phenomenon. This mechanism consists of three consecutive processes: initiation, multiplication, and amplification. Initiation is the mechano-chemical generation, by strong shaking following each dilution step, of radicals which remain in existence by mutual stabilization in simultaneously formed electronic domains. Multiplication transfers electronic excitation level structures from the original homeopathic agent to these radical-containing domains, stabilizing them further. …

Biochemical Characterization Of Human Mismatch Recognition Proteins Mutsα And Mutsβ, Lei Tian

University of Kentucky Doctoral Dissertations

The integrity of an organism's genome depends on the fidelity of DNA replication and the efficiency of DNA repair. The DNA mismatch repair (MMR) system, which is highly conserved from prokaryotes to eukaryotes, plays an important role in maintaining genome stability by correcting base-base mismatches and insertion/deletion (ID) mispairs generated during DNA replication and other DNA transactions. Mismatch recognition is a critical step in MMR. Two mismatch recognition proteins, MutSα (MSH2-MSH6 heterodimer) and MutSβ (MSH2-MSH3 heterodimer), have been identified in eukaryotic cells. MutSα and MutSβ have partially overlapping functions, with MutSα recognizing primarily base-base mismatches and 1-2 nt ID mispairs …

A Markov Transition Model To Dementia With Death As A Competing Event, Liou Xu

University of Kentucky Doctoral Dissertations

The research on multi-state Markov transition model is motivated by the nature of the longitudinal data from the Nun Study (Snowdon, 1997), and similar information on the BRAiNS cohort (Salazar, 2004). Our goal is to develop a flexible methodology for handling the categorical longitudinal responses and competing risks time-to-event that characterizes the features of the data for research on dementia. To do so, we treat the survival from death as a continuous variable rather than defining death as a competing absorbing state to dementia. We assume that within each subject the survival component and the Markov process are linked by …

Explorations In Homeoviscous Adaptation And Mass Spectral Analysis Of Membrane Lipids, Michael Douglas Timmons

University of Kentucky Doctoral Dissertations

The focus of this dissertation is centered on the mass spectral analysis of lipids and changes occurring in keeping with the concept of homeoviscous adaptation [1]. Homeoviscous adaptation is the process of modification of membrane lipids in response to environmental stimuli [1]. Dissertation investigations applied this concept to prokaryotic and eukaryotic organisms, and expanded the perception of environmental factors from exogenous organic solvents to intracellular environment.

The field of lipidomics deals with the analysis of phospholipid and fatty acid components of membranes the changes that occur due to environmental stimuli and their biological significance [2-6]. The high sensitivity of mass …

Development Of Novel Ahr Antagonists, Hyosung Lee

University of Kentucky Doctoral Dissertations

Aryl hydrocarbon receptor (AHR) is a sensor protein, activated by aromatic chemical species for transcriptionally regulating xenobiotic metabolizing enzymes. AHR is also known to be involved in a variety of pathogenesis such as cancer, diabetes mellitus, cirrhosis, asthma, etc. The AHR signaling induced by xenobiotics has been intensively studied whereas its physiological role in the absence of xenobiotics is poorly understood. Despite a number of ligands of AHR have been reported thus far, further applications are still hampered by the lack of specificity and/or the partially agonistic activity. Thus, a pure AHR antagonist is needed for deciphering the AHR cryptic …

Identification Of Neuroblastoma And Its Prognostic Markers Using Raman Spectroscopy, Rachel Kast

Wayne State University Dissertations

Introduction: Neuroblastoma is the most common cancer of infancy. It is one of several peripheral nervous system tumors, including ganglioneuroma, peripheral nerve sheath tumor, and pheochromocytoma. It is commonly situated on the adrenal gland. It displays similar histology to other small round blue cell tumors, including non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma. One method of judging neuroblastoma aggressiveness uses tumor histology factors, including mitosis-karyorrhexis index, Schwannian stromal development, degree of differentiation, and patient age. Tumor aggressiveness can also be judged based on the amplification of certain genes, including MYCN. Raman spectroscopy is a physics-based method which identifies the biochemical …

A Bland–Altman Comparison Of The Lead Care® System And Inductively Coupled Plasma Mass Spectrometry For Detecting Low-Level Lead In Child Whole Blood Samples, Christina Sobin, Tanner Schaub, Natali Parisi, Eva De La Riva

Christina Sobin, Ph.D.

Chronic childhood lead exposure, yielding blood lead levels consistently below 10 μg/dL, remains a major public health concern. Low neurotoxic effect thresholds have not yet been established. Progress requires accurate, efficient, and cost-effective methods for testing large numbers of children. The LeadCare® System (LCS) may provide one ready option. The comparability of this system to the “gold standard” method of inductively coupled plasma mass spectrometry (ICP-MS) for the purpose of detecting blood lead levels below 10 μg/dL has not yet been examined. Paired blood samples from 177 children ages 5.2–12.8 years were tested with LCS and ICP-MS. Triplicate repeat tests …

Bayesian Models And Decision Algorithms For Complex Early Phase Clinical Trials, Peter F. Thall

Peter F. Thall

No abstract provided.

Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull

Jeffrey S. Morris

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient …

Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris

Jeffrey S. Morris

A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.

Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …

Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang

Jeffrey S. Morris

Whilst recent progress in ‘shotgun’ peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS) has enabled its use as a sensitive analytical technique, proteome coverage and reproducibility is still limited and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates the continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data though spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly …

Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris

Jeffrey S. Morris

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. …

Code For Fitting Bdsacgh, Veera Baladandayuthapani

Veera Baladandayuthapani

No abstract provided.

R Package For Bayesian Ensemble Methods For Survival Prediction In Gene Expression Data, Veera Baladandayuthapani

Veera Baladandayuthapani

This is the R package for the methods described in Bayesian ensemble methods for survival prediction in gene expression data by Vinicius Bonato , Veerabhadran Baladandayuthapani, Kim-Anh Do, Bradley M. Broom, Erik P. Sulman, and Kenneth D. Aldape Submitted to Bioinformatics (2010)

Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veera Baladandayuthapani

Veera Baladandayuthapani

No abstract provided.

Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin

Paula Diehr

Background: Women with ovarian cancer have reported abdominal=pelvic pain, bloating, difficulty eating or feeling full quickly, and urinary frequency=urgency prior to diagnosis. We explored these findings in a general population using a dataset of insured women aged 40–64 and investigated the potential effectiveness of a routine review of claims data as a prescreen to identify women at high risk for ovarian cancer. Methods: Data from a large Washington State health insurer were merged with the Seattle-Puget Sound Surveillance, Epidemiology and End Results (SEER) cancer registry for 2000–2004. We estimated the prevalence of symptoms in the 36 months prior to diagnosis …

Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. Van Der Laan

Michael Rosenblum

Targeted maximum likelihood estimation is a versatile tool for estimating parameters in semiparametric and nonparametric models. We work through an example applying targeted maximum likelihood methodology to estimate the parameter of a marginal structural model. In the case we consider, we show how this can be easily done by clever use of standard statistical software. We point out differences between targeted maximum likelihood estimation and other approaches (including estimating function based methods). The application we consider is to estimate the effect of adherence to antiretroviral medications on virologic failure in HIV positive individuals.

Application Of Causal Inference Methods To Improve The Treatment Of Hiv In Resource-Limited Settings., Maya Petersen

Maya Petersen

No abstract provided.

Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh

Debashis Ghosh

In high-throughput studies involving genetic data such as from gene expression mi- croarrays, dierential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of dierential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing …

Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh

Debashis Ghosh

A recent nding in cancer research has been the characterization of previously undis- covered chromosomal abnormalities in several types of solid tumors. This was found based on analyses of high-throughput data from gene expression microarrays and motivated the development of so-called `outlier' tests for dierential expression. One statistical issue was the potential discreteness of the test statistics. Using ideas from fuzzy set theory, we develop fuzzy outlier detection algorithms that have links to ideas in multiple comparisons. Two- and K-sample extensions are considered. The methodology is illustrated by application to two microarray studies.

Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott

Debashis Ghosh

There has been substantive interest in the assessment of surrogate endpoints in medical research. These are measures which could potentially replace \true" endpoints in clinical trials and lead to studies that require less follow-up. Recent research in the area has focused on assessments using causal inference frameworks. Beginning with a simple model for associating the surrogate and true endpoints in the population, we approach the problem as one of endogenous covariates. An instrumental variables estimator and general two-stage algorithm is proposed. Existing surrogacy frameworks are then evaluated in the context of the model. A numerical example is used to illustrate …

Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent

Debashis Ghosh

There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using meta-analytical methods for quanti cation of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semi-competing risks setting, where we constrain the surrogate endpoint to occur before the true endpoint. A novel principal components procedure is …

Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel

Debashis Ghosh

A biomarker is dened to be a biological characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The use of biomarkers in cancer has been advocated for a variety of purposes, which include use as surrogate endpoints, early detection of disease, proxies for environmental exposure and risk prediction. We deal with the latter issue in this paper. Several authors have proposed use of the predictiveness curve for assessing the capacity of a biomarker for risk prediction. For most situations, it is reasonable to assume monotonicity of …