Computer Sciences Commons^™

Cutaneous Malignant Melanoma Incidences Analyzed Worldwide By Skin Type Over Advancing Age Of Males And Females: Evidence Estrogen And Androgenic Hair Are Risk Factors, Dianne E. Godar, Madhan Subramanian, Stephen Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

We previously analyzed cutaneous malignant melanoma (CMM) incidences worldwide by sex, age, and Fitzpatrick skin type over time (1955-2007) and found only European-ancestry populations have exponential increasing incidences and about a 2-log increase in the risk between the youngest age groups (0-14 and 15-29 yr). We proposed the increasing incidence over time may be from the spread of Human Papilloma Virus (HPV) found in CMM biopsies, and that the 2-log incidence increase between the youngest age groups might be from developing androgenic hair. The increasing incidence with age may be from white hairs transmitting UV radiation to follicular melanocytes. Here …

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 …

All Sites But Skin Cancer Incidences Analyzed Worldwide By Sex, Age, And Skin Type Over Time (1955-2007), Advancing Age, And Uvb Dose Reveals Important Carcinogenic Drivers, Dianne E. Godar, Rossen Gurov, Stephen Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

Because we observed increasing incidences over time, advancing age, higher estrogen levels, decreasing UVB (290-315 nm) doses, or lower vitamin D₃, and Human Papillomavirus hiding in immune-privileged sites of hair follicles play roles in melanoma, we wondered if the majority of cancers might have similar carcinogenic drivers. To investigate this possibility, we performed worldwide analysis of all sites but skin cancer over time (1955-2007), advancing age, and UVB doses for males and females with all skin types and ages (0-85+) and in five age groups using IARC data. To investigate Human Papillomavirus’s role, we analyzed the incidences of …

Processdriver: A Computational Pipeline To Identify Copy Number Drivers And Associated Disrupted Biological Processes In Cancer, Brittany Baur, Serdar Bozdag

Mathematics, Statistics and Computer Science Faculty Research and Publications

Copy number amplifications and deletions that are recurrent in cancer samples harbor genes that confer a fitness advantage to cancer tumor proliferation and survival. One important challenge in computational biology is to separate the causal (i.e., driver) genes from passenger genes in large, aberrated regions. Many previous studies focus on the genes within the aberration (i.e., cis genes), but do not utilize the genes that are outside of the aberrated region and dysregulated as a result of the aberration (i.e., trans genes). We propose a computational pipeline, called ProcessDriver, that prioritizes candidate drivers by relating cis genes to …

Characterizations Of Kumaraswamy-Laplace, Mcdonald Inverse Weibull And New Generalized Exponential Distributions, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Nassar (2016) considers an interesting univariate continuous distribution called Kumaraswamy-Laplace which has different forms on two subintervals. He studies certain properties and applications of this distribution. Shahbaz et al. (2016) consider another interesting distribution called McDonald Inverse Weibull distribution. They present some basic properties of their distribution and study the estimations of the parameters as well as discussing its application via an illustrative example. What is lacking in both papers, in our opinion, is the characterizations of these two interesting distributions. the present work is intended to complete, in some way, the works of Nassar and Shahbaz et al. via …

Varieties Of Restriction Semigroups And Varieties Of Categories, Peter R. Jones

Mathematics, Statistics and Computer Science Faculty Research and Publications

The variety of restriction semigroups may be most simply described as that generated from inverse semigroups (S, ·, −1) by forgetting the inverse operation and retaining the two operations x+ = xx−1 and x* = x−1x. The subvariety B of strictrestriction semigroups is that generated by the Brandt semigroups. At the top of its lattice of subvarieties are the two intervals [B2, B2M = B] and [B0, B0M]. Here, B2and B0 are, respectively, generated by the five-element Brandt semigroup and that obtained …

Extremal H-Colorings Of Trees And 2-Connected Graphs, John Engbers, David Galvin

Mathematics, Statistics and Computer Science Faculty Research and Publications

For graphs G and H, an H-coloring of G is an adjacency preserving map from the vertices of G to the vertices of H. H-colorings generalize such notions as independent sets and proper colorings in graphs. There has been much recent research on the extremal question of finding the graph(s) among a fixed family that maximize or minimize the number of H-colorings. In this paper, we prove several results in this area.

First, we find a class of graphs H with the property that for each H∈H, the n-vertex tree that minimizes the number of …

Protein Structure Classification And Loop Modeling Using Multiple Ramachandran Distributions, Seyed Morteza Najibi, Mehdi Maadooliat, Lan Zhou, Jianhua Z. Huang, Xin Gao

Mathematics, Statistics and Computer Science Faculty Research and Publications

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. …

Cutaneous Malignant Melanoma Incidences Analyzed Worldwide By Sex, Age, And Skin Type Over Personal Ultraviolet-B Dose Shows No Role For Sunburn But Implies One For Vitamin D3, Dianne E. Godar, Madhan Subramanian, Stephen Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

Because the incidence of cutaneous malignant melanoma (CMM) was reported to increase with increasing terrestrial UVR (290–400 nm) doses in the US back in 1975 and a recent publication showed no association exists with UVR exposure at all, we set out to fully elucidate the role of UVR in CMM. To achieve this goal, we analyzed the CMM incidences over latitude and estimated the average personal UVR dose in the US and numerous countries (> 50) on 5 continents around the world. Using data from the International Agency for Research on Cancer in 2005, we performed worldwide analysis of CMM …

Untangling The Most Probable Role For Vitamin D3 In Autism, Dianne E. Godar, Stephen J. Merrill

Mathematics, Statistics and Computer Science Faculty Research and Publications

Recent studies indicate an important role for vitamin D₃ in autism spectrum disorder (ASD), although its mechanism is not completely understood. The most puzzling aspect of ASD is that identical twins, who share identical DNA, do not have 100% concordance rates (∼88% for identical and ∼31% for fraternal twins). These findings provide major clues into the etiology: ASD must involve an environmental factor present in the prenatal milieu that both identical twins are not always exposed to because they do not always share it (i.e., placentas). Combined with the exponential increasing rates of ASD around the world, these observations …

Mapping The Stk4/Hippo Signaling Network In Prostate Cancer Cell, Damien Ready, Kader Yagiz, Pooneh Amin, Yuksel Yildiz, Vincent Funari, Serdar Bozdag, Bekir Cinar

Mathematics, Statistics and Computer Science Faculty Research and Publications

Dysregulation of MST1/STK4, a key kinase component of the Hippo-YAP pathway, is linked to the etiology of many cancers with poor prognosis. However, how STK4 restricts the emergence of aggressive cancer remains elusive. Here, we investigated the effects of STK4, primarily localized in the cytoplasm, lipid raft, and nucleus, on cell growth and gene expression in aggressive prostate cancer. We demonstrated that lipid raft and nuclear STK4 had superior suppressive effects on cell growth in vitro and in vivo compared with cytoplasmic STK4. Using RNA sequencing and bioinformatics analysis, we identified several differentially expressed (DE) genes that responded to ectopic …

Nature Of Mathematical Modeling Tasks For Secondary Mathematics Preservice Teachers, Jia He, Eryn Stehr, Hyunyi Jung

Mathematics, Statistics and Computer Science Faculty Research and Publications

This study investigated the nature of written modeling tasks reported by instructors of required courses in five secondary mathematics teacher education programs. These tasks were analyzed based on a framework addressing potential cognitive orientation (simple procedures, complex procedures, and rich tasks) and purpose (epistemological, educational, contextual, and socio-critical modeling) of the tasks. Our analysis suggests that most tasks included questions of more than one cognitive orientation and more than half of the tasks were coded as contextual modeling. We also found that tasks that were coded as contextual modeling offered opportunities for future teachers to engage with questions at all …

Some Extended Classes Of Distributions: Characterizations And Properties, Gholamhossein G. Hamedani, Gauss M. Cordeiro, M. C.S. Lima, A. D.C. Nascimento

Mathematics, Statistics and Computer Science Faculty Research and Publications

Based on a simple relationship between two truncated moments and certain functions of the th order statistic, we characterize some extended classes of distributions recently proposed in the statistical literature, videlicet Beta-G, Gamma-G, Kumaraswamy-G and McDonald-G. Several properties of these extended classes and some special cases are discussed. We compare these classes in terms of goodness-of-fit criteria using some baseline distributions by means of two real data sets.

Hypothesis Testing For High-Dimensional Problems, Naveen K. Bansal

Mathematics, Statistics and Computer Science Faculty Research and Publications

For high-dimensional hypothesis problems, new approaches have emerged since the publication. The most promising of them uses Bayesian approach. In this chapter, we review some of the past approaches applicable to only law-dimensional hypotheses testing and contrast it with the modern approaches of high-dimensional hypotheses testing. We review some of the new results based on Bayesian decision theory and show how Bayesian approach can be used to accommodate directional hypotheses testing and skewness in the alternatives. A real example of gene expression data is used to demonstrate a Bayesian decision theoretic approach to directional hypotheses testing with skewed alternatives.

A Short Note On The Paper: "New Characterizations Of The Pareto Distribution", Gholamhossein G. Hamedani, M. Rasekhi

Mathematics, Statistics and Computer Science Faculty Research and Publications

Nofal and El Gebaly (2017), presented certain characterizations of the Pareto distribution based on the conditional expectations of power of the order statistics. In this short note we show that the same results can easily be obtained in terms of the power of the random variable.

Privacy Vulnerabilities In The Practices Of Repairing Broken Digital Artifacts In Bangladesh, Syed Ishtiaque Ahmed, Shion Guha, Mohammad Rashidujjaman Rifat, Faysal Hossain Shezan, Nicola Dell

Mathematics, Statistics and Computer Science Faculty Research and Publications

This paper presents a study on the privacy concerns associated with the practice of repairing broken digital objects in Bangladesh. Historically, repair of old or broken technologies has received less attention in ICTD scholarship than design, development, or use. As a result, the potential privacy risks associated with repair practices have remained mostly unaddressed. This paper describes our three-month long ethnographic study that took place at ten major repair sites in Dhaka, Bangladesh. We show a variety of ways in which the privacy of an individual’s personal data may be compromised during the repair process. We also examine people’s perceptions …

K-8 Pre-Service Teachers’ Algebraic Thinking: Exploring The Habit Of Mind Building Rules To Represent Functions, Marta T. Magiera, John C. Moyer, Leigh A. Van Den Kieboom

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this study, through the lens of the algebraic habit of mind Building Rules to Represent Functions, we examined 18 pre-service middle school teachers' ability to use algebraic thinking to solve problems. The data revealed that pre-service teachers' ability to use different features of the habit of mind Building Rules to Represent Functions varied across the features. Significant correlations existed between 8 pairs of the features. The ability to justify a rule was the weakest of the seven features and it was correlated with the ability to chunk information. Implications for mathematics teacher education are discussed.

Xinupi3: Teaching Multicore Concepts Using Embedded Xinu, Priva Bansal, Rade Latinovich, Tom Lazar, Patrick J. Mcgee, Dennis Brylow

Mathematics, Statistics and Computer Science Faculty Research and Publications

As computer platforms become more advanced, the need to teach advanced computing concepts grows accordingly. This paper addresses one such need by presenting XinuPi3, a port of the lightweight instructional operating system Embedded Xinu to the Raspberry Pi 3. The Raspberry Pi 3 improves upon previous generations of inexpensive, credit card-sized computers by including a quad-core, ARM-based processor, opening the door for educators to demonstrate essential aspects of modern computing like inter-core communication and genuine concurrency.

Embedded Xinu has proven to be an effective teaching tool for demonstrating low-level concepts on single-core platforms, and it is currently used to …

On Comparative Algorithmic Pathfinding In Complex Networks For Resource-Constrained Software Agents, Michael Moran

Walden Dissertations and Doctoral Studies

Software engineering projects that utilize inappropriate pathfinding algorithms carry a

significant risk of poor runtime performance for customers. Using social network theory,

this experimental study examined the impact of algorithms, frameworks, and map

complexity on elapsed time and computer memory consumption. The 1,800 2D map

samples utilized were computer random generated and data were collected and processed

using Python language scripts. Memory consumption and elapsed time results for each of

the 12 experimental treatment groups were compared using factorial MANOVA to

determine the impact of the 3 independent variables on elapsed time and computer

memory consumption. The MANOVA indicated a …

Human-Intelligence/Machine-Intelligence Decision Governance: An Analysis From Ontological Point Of View, Faisal Mahmud, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

The increasing CPU power and memory capacity of computers, and now computing appliances, in the 21st century has allowed accelerated integration of artificial intelligence (AI) into organizational processes and everyday life. Artificial intelligence can now be found in a wide range of organizational processes including medical diagnosis, automated stock trading, integrated robotic production systems, telecommunications routing systems, and automobile fuzzy logic controllers. Self-driving automobiles are just the latest extension of AI. This thrust of AI into organizations and everyday life rests on the AI community’s unstated assumption that “…every aspect of human learning and intelligence could be so precisely described …

Modeling Volatility Of Financial Time Series Using Arc Length, Benjamin H. Hoerlein

College of Graduate Studies: Theses & Dissertations

This thesis explores how arc length can be modeled and used to measure the risk involved with a financial time series. Having arc length as a measure of volatility can help an investor in sorting which stocks are safer/riskier to invest in. A Gamma autoregressive model of order one(GAR(1)) is proposed to model arc length series. Kernel regression based bias correction is studied when model parameters are estimated using method of moment procedure. As an application, a model-based clustering involving thirty different stocks is presented using k-means++ and hierarchical clustering techniques.

An Effective Computational Method Incorporating Multiple Secondary Structure Predictions In Topology Determination For Cryo-Em Images, Abhishek Biswas, Desh Ranjan, Mohammad Zubair, Stephanie Zeil, Kamal Al Nasr, Jing He

Computer Science Faculty Publications

A key idea in de novo modeling of a medium-resolution density image obtained from cryo-electron microscopy is to compute the optimal mapping between the secondary structure traces observed in the density image and those predicted on the protein sequence. When secondary structures are not determined precisely, either from the image or from the amino acid sequence of the protein, the computational problem becomes more complex. We present an efficient method that addresses the secondary structure placement problem in presence of multiple secondary structure predictions and computes the optimal mapping. We tested the method using 12 simulated images from alpha-proteins and …

Non Markovian Queue With Two Types Service Optional Re-Service And General Vacation Distribution, K. Sathiya, G. Ayyappan

Applications and Applied Mathematics: An International Journal (AAM)

We consider a single server batch arrival queueing system, where the server provides two types of heterogeneous service. A customer has the option of choosing either type 1 service with probability p1 or type 2 service with probability p2 with the service times follow general distribution. After the completion of either type 1 or type 2 service a customer has the option to repeat or not to repeat the type 1 or type 2 service. As soon as the customer service is completed, the server will take a vacation with probability θ or may continue staying in the system with …

Applying Ahp And Clustering Approaches For Public Transportation Decisionmaking: A Case Study Of Isfahan City, Alireza Salavati, Hossein Haghshenas, Bahador Ghadirifaraz, Jamshid Laghaei, Ghodrat Eftekhari

Journal of Public Transportation

The main purpose of this paper is to define appropriate criteria for the systematic approach to evaluate and prioritize multiple candidate corridors for public transport investment simultaneously to serve travel demand, regarding supply of current public transportation system and road network conditions of Isfahan, Iran. To optimize resource allocation, policymakers need to identify proper corridors to implement a public transportation system. In fact, the main question is to adopt the best public transportation system for each main corridor of Isfahan. In this regard, 137 questionnaires were completed by experts, directors, and policymakers of Isfahan to identify goals and objectives in …

Computational Environment For Modeling And Analysing Network Traffic Behaviour Using The Divide And Recombine Framework, Ashrith Barthur

Open Access Dissertations

There are two essential goals of this research. The first goal is to design and construct a computational environment that is used for studying large and complex datasets in the cybersecurity domain. The second goal is to analyse the Spamhaus blacklist query dataset which includes uncovering the properties of blacklisted hosts and understanding the nature of blacklisted hosts over time.

The analytical environment enables deep analysis of very large and complex datasets by exploiting the divide and recombine framework. The capability to analyse data in depth enables one to go beyond just summary statistics in research. This deep analysis is …

A Framework For The Statistical Analysis Of Mass Spectrometry Imaging Experiments, Kyle Bemis

Open Access Dissertations

Mass spectrometry (MS) imaging is a powerful investigation technique for a wide range of biological applications such as molecular histology of tissue, whole body sections, and bacterial films , and biomedical applications such as cancer diagnosis. MS imaging visualizes the spatial distribution of molecular ions in a sample by repeatedly collecting mass spectra across its surface, resulting in complex, high-dimensional imaging datasets. Two of the primary goals of statistical analysis of MS imaging experiments are classification (for supervised experiments), i.e. assigning pixels to pre-defined classes based on their spectral profiles, and segmentation (for unsupervised experiments), i.e. assigning pixels to newly …

Divide And Recombined For Large Complex Data: Nonparametric-Regression Modelling Of Spatial And Seasonal-Temporal Time Series, Xiaosu Tong

Open Access Dissertations

In the first chapter of this dissertation, I briefly introduce one type of nonparametric regression method, namely local polynomial regression, followed by emphasis on one specific application of loess on time series decomposition, called Seasonal Trend Loess (STL). The chapter is closed by the introduction of D\&R; (Divide and Recombined) statistical framework. Data can be divided into subsets, each of which is applied with a statistical analysis method. This is an embarrassing parallel procedure since there is no communication between each subset. Then the analysis result for each subset are combined together to be the final analysis outcome for the …

Impact Of Myh6 Variants In Hypoplastic Left Heart Syndrome, Aoy Tomita-Mitchell, Karl D. Stamm, Donna K. Mahnke, Min-Su Kim, Pip M. Hidestrand, Huan-Ling Liang, Mary A. Goetsch, Mats Hidestrand, Pippa Simpson, Andrew N. Pelech, James S. Tweddell, D. Woodrow Benson, John Lough, Michael Mitchell

Mathematics, Statistics and Computer Science Faculty Research and Publications

Hypoplastic left heart syndrome (HLHS) is a clinically and anatomically severe form of congenital heart disease (CHD). Although prior studies suggest that HLHS has a complex genetic inheritance, its etiology remains largely unknown. The goal of this study was to characterize a risk gene in HLHS and its effect on HLHS etiology and outcome. We performed next-generation sequencing on a multigenerational family with a high prevalence of CHD/HLHS, identifying a rare variant in the α-myosin heavy chain (MYH6) gene. A case-control study of 190 unrelated HLHS subjects was then performed and compared with the 1000 Genomes Project. Damaging …

The Decay Of Disease Association With Declining Linkage Disequilibrium: A Fine Mapping Theorem, Mehdi Maadooliat, Naveen K. Bansal, Jibal Upadhya, Manzur R. Farazi, Xiang Li, Max M. He, Scott J. Hebbring, Zhan Ye, Steven J. Schrodi

Mathematics, Statistics and Computer Science Faculty Research and Publications

Several important and fundamental aspects of disease genetics models have yet to be described. One such property is the relationship of disease association statistics at a marker site closely linked to a disease causing site. A complete description of this two-locus system is of particular importance to experimental efforts to fine map association signals for complex diseases. Here, we present a simple relationship between disease association statistics and the decline of linkage disequilibrium from a causal site. Specifically, the ratio of Chi-square disease association statistics at a marker site and causal site is equivalent to the standard measure of pairwise …

Impact Of Myh6 Variants In Hypoplastic Left Heart Syndrome, Aoy Tomita-Mitchell, Karl D. Stamm, Donna K. Mahnke, Min-Su Kim, Pip M. Hidestrand, Huan-Ling Liang, Mary Goetsch, Pippa Simpson, Andrew N. Pelech, James S. Tweddell, D. Woodrow Benson, John Lough, Michael E. Mitchell

Mathematics, Statistics and Computer Science Faculty Research and Publications

Hypoplastic left heart syndrome (HLHS) is a clinically and anatomically severe form of congenital heart disease (CHD). Although prior studies suggest that HLHS has a complex genetic inheritance, its etiology remains largely unknown. The goal of this study was to characterize a risk gene in HLHS and its effect on HLHS etiology and outcome. We performed next-generation sequencing on a multigenerational family with a high prevalence of CHD/HLHS, identifying a rare variant in the α-myosin heavy chain (MYH6) gene. A case-control study of 190 unrelated HLHS subjects was then performed and compared with the 1000 Genomes Project. Damaging …