Numerical Analysis and Scientific Computing Commons^™

Evaluation Of Essential Genes In Correlation Networks Using Measures Of Centrality, Kathryn Dempsey Cooper, Hesham Ali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Correlation networks are emerging as powerful tools for modeling relationships in high-throughput data such as gene expression. Other types of biological networks, such as protein-protein interaction networks, are popular targets of study in network theory, and previous analysis has revealed that network structures identified using graph theoretic techniques often relate to certain biological functions. Structures such as highly connected nodes and groups of nodes have been found to correspond to essential genes and protein complexes, respectively. The correlation network, which measures the level of co-variation of gene expression levels, shares some structural properties with other types of biological networks. We …

A Novel Correlation Networks Approach For The Identification Of Gene Targets, Kathryn Dempsey Cooper, Stephen Bonasera, Dhundy Raj Bastola, Hesham Ali

Interdisciplinary Informatics Faculty Proceedings & Presentations

Correlation networks are emerging as a powerful tool for modeling temporal mechanisms within the cell. Particularly useful in examining coexpression within microarray data, studies have determined that correlation networks follow a power law degree distribution and thus manifest properties such as the existence of “hub” nodes and semicliques that potentially correspond to critical cellular structures. Difficulty lies in filtering coincidental relationships from causative structures in these large, noise-heavy networks. As such, computational expenses and algorithm availability limit accurate comparison, making it difficult to identify changes between networks. In this vein, we present our work identifying temporal relationships from microarray data …

A Noise Reducing Sampling Approach For Uncovering Critical Properties In Large Scale Biological Networks, Karthik Duraisamy, Kathryn Dempsey Cooper, Hesham Ali, Sanjukta Bhowmick

Interdisciplinary Informatics Faculty Proceedings & Presentations

A correlation network is a graph-based representation of relationships among genes or gene products, such as proteins. The advent of high-throughput bioinformatics has resulted in the generation of volumes of data that require sophisticated in silico models, such as the correlation network, for in-depth analysis. Each element in our network represents expression levels of multiple samples of one gene and an edge connecting two nodes reflects the correlation level between the two corresponding genes in the network according to the Pearson correlation coefficient. Biological networks made in this manner are generally found to adhere to a scale-free structural nature, that …

Housing With Support Marketing Study Tool, Gary M. Travis

All Graduate Theses, Dissertations, and Other Capstone Projects

Housing for persons with serious mental illness (SMI) that is permanent, affordable, and supportive is very limited because the availability of these resources is inadequate and subject to significant demand by persons that are disabled or on a limited income. The limited access to housing for persons with SMI is contributing to homelessness and Minnesota has seen a steady rise since 1994 in the rate and number of people that are homeless and coping with mental illness (Wilder Research, 2010a). While some of the impact of disability, homelessness, and limited affordable housing access is known, what remains uncertain is a …

Why Is An Einstein Ring Blue?, Jonathan Blackledge

Articles

Albert Einstein predicted the existence of `Einstein rings' as a consequence of his general theory of relativity. The phenomenon is a direct result of the idea that if a mass warps space-time then light (and other electromagnetic waves) will be `lensed' by the strong gravitational field produced by a large cosmological body such as a galaxy. Since 1998, when the first complete Einstein ring was observed, many more complete or partially complete Einstein rings have been observed in the radio and infrared spectra, for example, and by the Hubble Space Telescope in the optical spectrum. However, in the latter case, …

Real-Time Road Traffic Prediction With Spatio-Temporal Correlations, Wanli Min, Laura Wynter

Research Collection School Of Computing and Information Systems

Real-time road traffic prediction is a fundamental capability needed to make use of advanced, smart transportation technologies. Both from the point of view of network operators as well as from the point of view of travelers wishing real-time route guidance, accurate short-term traffic prediction is a necessary first step. While techniques for short-term traffic prediction have existed for some time, emerging smart transportation technologies require the traffic prediction capability to be both fast and scalable to full urban networks. We present a method that has proven to be able to meet this challenge. The method presented provides predictions of speed …

Automatic Media Segmentation Within Ieee 1599–2008, Antonello D'Aguanno, Luca A. Ludovico, Davide Andrea Mauro

Computer Sciences and Electrical Engineering Faculty Research

This paper deals with the automatic extraction of synchronization data from IEEE 1599-2008, an XML-based standard aiming at a comprehensive description of music. Within such format, audio tracks and video contents related to the same music piece can be referred to the occurrence of symbolic music events. In this way, digital objects are mutually synchronized, too. The goal is to show how timing information can be easily extracted from an IEEE 1599-2008 file, converted into a suitable format, and finally employed in a multimedia editing environment in order to produce an automatic segmentation of media objects.

Appearance Based Stage Recognition Of Drosophila Embryos, Gopi Chand Nutakki

Masters Theses & Specialist Projects

Stages in Drosophila development denote the time after fertilization at which certain specific events occur in the developmental cycle. Stage information of a host embryo, as well as spatial information of a gene expression region is indispensable input for the discovery of the pattern of gene-gene interaction. Manual labeling of stages is becoming a bottleneck under the circumstance of high throughput embryo images. Automatic recognition based on the appearances of embryos is becoming a more desirable scheme. This problem, however, is very challenging due to severe variations of illumination and gene expressions. In this research thesis, we propose an appearance …

The R Journal (December 2010) 2(2): Complete Issue, The R Foundation

The R Journal

Contributed Research Articles

Solving Differential Equations in R, Karline Soetaert, Thomas Petzoldt and R. Woodrow Setzer

Source References, Duncan Murdoch

hglm: A Package for Fitting Hierarchical Generalized Linear Models, Lars Rönnegård, Xia Shen and Moudud Alam

dclone: Data Cloning in R, Péter Sólymos

stringr: Modern, Consistent String Processing, Hadley Wickham

Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations, David Ardia and Lennart F. Hoogerheide

cudaBayesreg: Bayesian Computation in CUDA, Adelino Ferreira da Silva

binGroup: A Package for Group Testing, Christopher R. Bilder, Boan Zhang, Frank Schaarschmidt, and Joshua M. Tebbs

The RecordLinkage Package: Detecting Errors in Data, Murat Sariyar …

The Recordlinkage Package: Detecting Errors In Data, Murat Sariyar, Andreas Borg

The R Journal

Record linkage deals with detecting homonyms and mainly synonyms in data. The package RecordLinkage provides means to per form and evaluate different record linkage methods. A stochastic framework is implemented which calculates weights through an EM algorithm. The determination of the necessary thresholds in this model can be achieved by tools of extreme value theory. Furthermore, machine learning methods are utilized, including decision trees (rpart), bootstrap aggregating (bagging), ada boost (ada), neural nets (nnet) and support vector machines (svm). The generation of record pairs and comparison patterns from single data …

Bingroup: A Package For Group Testing, Christopher R. Bilder, Boan Zhang, Frank Schaarschmidt, Joshua M. Tebbs

The R Journal

When the prevalence of a disease or of some other binary characteristic is small, group testing (also known as pooled testing) is frequently used to estimate the prevalence and/or to identify individuals as positive or negative. We have developed the binGroup package as the first package designed to address the estimation problem in group testing. We present functions to estimate an overall prevalence for a homogeneous population. Also, for this set ting, we have functions to aid in the very important choice of the group size. When individuals come from a heterogeneous population, our group testing regression functions can be …

Stringr: Modern, Consistent String Processing, Hadley Wickham

The R Journal

String processing is not glamorous, but it is frequently used in data cleaning and preparation. The existing string functions in R are powerful, but not friendly. To remedy this, the stringr package provides string functions that are simpler and more consistent, and also fixes some functionality that R is missing compared to other programming languages.

Source References, Duncan Murdoch

The R Journal

Since version 2.10.0, R includes expanded support for source references in R code and ‘.Rd’ files. This paper describes the origin and purposes of source references, and current and future support for them.

Mapping And Measuring Country Shapes, Nils B. Weidmann, Kristian Skrede Gleditsch

The R Journal

The article introduces the cshapes R package, which includes our CShapes dataset of contemporary and historical country boundaries, as well as computational tools for computing geographical measures from these maps. We provide an overview of the need for considering spatial dependence in comparative re search, how this requires appropriate historical maps, and detail how the cshapes associated R package cshapes can contribute to these ends. We illustrate the use of the package for drawing maps, computing spatial variables for countries, and generating weights matrices for spatial statistics.

Dclone: Data Cloning In R, Péter Sólymos

The R Journal

The dclone R package contains low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov Chain Monte Carlo methods with support for JAGS, WinBUGS and OpenBUGS.

Solving Differential Equations In R, Karline Soetaert, Thomas Petzoldt, R. Woodrow Setzer

The R Journal

Although R is still predominantly applied for statistical analysis and graphical representation, it is rapidly becoming more suitable for mathematical computing. One of the fields where considerable progress has been made recently is the solution of differential equations. Here we give a brief overview of differential equations that can now be solved by R.

Spikeslab: Prediction And Variable Selection Using Spike And Slab Regression, Hemant Ishwaran, Udaya B. Kogalur, J. Sunil Rao

The R Journal

Weighted generalized ridge regression offers unique advantages in correlated high dimensional problems. Such estimators can be efficiently computed using Bayesian spike and slab models and are effective for prediction. For sparse variable selection, a generalization of the elastic net can be used in tandem with these Bayesian estimates. In this article, we de scribe the R-software package spikeslab for implementing this new spike and slab prediction and variable selection methodology.

Hglm: A Package For Fitting Hierarchical Generalized Linear Models, Lars Rönnegård, Xia Shen, Moudud Alam

The R Journal

We present the hglm package for fit ting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

Bayesian Estimation Of The Garch(1,1) Model With Student-T Innovations, David Ardia, Lennart F. Hoogerheide

The R Journal

This note presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the tedious task of tuning an MCMC sampling algorithm. The usage of the package is shown in an empirical application to exchange rate log-returns

Online Reproducible Research: An Application To Multivariate Analysis Of Bacterial Dna Fingerprint Data, Jean Thioulouse, Claire Valiente-Moro, Lionel Zenner

The R Journal

This paper presents an example of online reproducible multivariate data analysis. This example is based on a web page providing an online computing facility on a server. HTML forms contain editable R code snippets that can be executed in any web browser thanks to the Rweb software. The example is based on the multivariate analysis of DNA fingerprints of the internal bacterial flora of the poultry red mite Dermanyssus gallinae. Several multivariate data analysis methods from the ade4 package are used to compare the fingerprints of mite pools coming from various poultry farms. All the computations and graphical displays …