Computer Sciences Commons^™

Isogenegui: Multiple Approaches For Dose-Response Analysis Of Microarray Data Using R, Martin Otava, Rudradev Sengupta, Ziv Shkedy, Dan Lin, Setia Pramana, Tobias Verbeke, Philippe Haldermans, Ludwig A. Hothorn, Daniel Gerhard, Rebecca M. Kuiper, Florian Klinglmueller, Adetayo Kasim

The R Journal

The analysis of transcriptomic experiments with ordered covariates, such as dose-response data, has become a central topic in bioinformatics, in particular in omics studies. Consequently, multiple R packages on CRAN and Bioconductor are designed to analyse microarray data from various perspectives under the assumption of order restriction. We introduce the new R package IsoGene Graphical User Interface (IsoGeneGUI), an extension of the original IsoGene package that includes methods from most of available R packages designed for the analysis of order restricted microarray data, namely orQA, ORIClust, goric and ORCME. The methods included in the new …

Gsympoint: An R Package To Estimate The Generalized Symmetry Point, An Optimal Cut-Off Point For Binary Classification In Continuous Diagnostic Tests, Mónica López-Ratón, Elisa M. Molanes-López, Emilio Letón, Carmen Cadarso-Suárez

The R Journal

In clinical practice, it is very useful to select an optimal cutpoint in the scale of a continuous biomarker or diagnostic test for classifying individuals as healthy or diseased. Several methods for choosing optimal cutpoints have been presented in the literature, depending on the ultimate goal. One of these methods, the generalized symmetry point, recently introduced, generalizes the symmetry point by incorporating the misclassification costs. Two statistical approaches have been proposed in the literature for estimating this optimal cutpoint and its associated sensitivity and specificity measures, a parametric method based on the generalized pivotal quantity and a nonparametric method based …

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

The Bioconductor project provides tools for the analysis and comprehension of high throughput genomic data. Bioconductor 3.5 was released on 25 April, 2017. It is compatible with R 3.4 and consists of 1383 software packages, 316 experiment data packages, and 911 up-to-date annotation packages. The release announcement includes descriptions of 88 new packages, and updated NEWS files for many additional packages. Start using Bioconductor by installing the most recent version of R and evaluating the commands

Bayesbinmix: An R Package For Model Based Clustering Of Multivariate Binary Data, Panagiotis Papastamoulis, Magnus Rattray

The R Journal

The BayesBinMix package offers a Bayesian framework for clustering binary data with or without missing values by fitting mixtures of multivariate Bernoulli distributions with an unknown number of components. It allows the joint estimation of the number of clusters and model parameters using Markov chain Monte Carlo sampling. Heated chains are run in parallel and accelerate the convergence to the target posterior distribution. Identifiability issues are addressed by implementing label switching algorithms. The package is demonstrated and benchmarked against the Expectation Maximization algorithm using a simulation study as well as a real dataset.

Geometry-Based Mass Grading Of Mango Fruits Using Image Processing, M. A. Momin, Md Towfiqur Rahman, M. S. Sultana, C. Igathinathane, A. T. M. Ziauddin, T. E. Grift

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Mango (Mangifera indica) is an important, and popular fruit in Bangladesh. However, the post-harvest processing of it is still mostly performed manually, a situation far from satisfactory, in terms of accuracy and throughput. To automate the grading of mangos (geometry and shape), we developed an image acquisition and processing system to extract projected area, perimeter, and roundness features. In this system, images were acquired using a XGA format color camera of 8-bit gray levels using fluorescent lighting. An image processing algorithm based on region based global thresholding color binarization, combined with median filter and morphological analysis was developed …

Plant Image Processing: 3d Volume Reconstruction, Hyperspectral Information Mining And Visualization, Shi Cao

School of Computing: Dissertations, Theses, and Student Research

Image processing techniques have been widely used in plant science for plant phenotyping studies. These fast algorithms are desired to process massive image data. In this thesis, we analyze RGB digital images taken from different view angles of plants and propose an efficient ad-hoc algorithm to identify structures of plants by 3D volume reconstruction techniques. We study hyperspectral images of plants and extend our scope to other images from different scientific disciplines. Obtaining the spectral and spatial information simul- taneously is a challenging task due to the high dimensionality of hyperspectral images. We first develop a real-time interactive tool for …

Hierarchical Active Learning Application To Mitochondrial Disease Protein Dataset, James D. Duin

School of Computing: Dissertations, Theses, and Student Research

This study investigates an application of active machine learning to a protein dataset developed to identify the source of mutations which give rise to mitochondrial disease. The dataset is labeled according to the protein's location of origin in the cell; whether in the mitochondria or not, or a specific target location in the mitochondria's outer or inner membrane, its matrix, or its ribosomes. This dataset forms a labeling hierarchy. A new machine learning approach is investigated to learn the high-level classifier, i.e., whether the protein is a mitochondrion, by separately learning finer-grained target compartment concepts and combining the results. This …

The Economics Of The Right To Be Forgotten, Byung-Cheol Kim, Jin Yeub Kim

Department of Economics: Faculty Publications

Scholars and practitioners debate whether to expand the scope of the right to be forgotten—the right to have certain links removed from search results—to encompass global search results. The debate centers on the assumption that the expansion will increase the incidence of link removal, which reinforces privacy while hampering free speech. We develop a game-theoretic model to show that the expansion of the right to be forgotten can reduce the incidence of link removal. We also show that the expansion does not necessarily enhance the welfare of individuals who request removal and that it can either improve or reduce societal …

Aerial Water Sampler, Carrick Detweiler, John-Paul Ore, Baoliang Zhao, Sebastian Elbaum

School of Computing: Faculty Publications

In one aspect, a vehicle includes an aerial propulsion system, an altitude sensor system, a water sampling system, and a control system. The water sampling system includes a water sampling extension configured to extend away from the vehicle, one or more water sample receptacles, and a water pump. The control system is configured to perform operations including: guiding, using the aerial propulsion system, the vehicle over a water Source; causing, using sensor data from the altitude sensor system, the vehicle to descend towards the water source so that the water sampling extension contacts the water source; and causing, using the …

Women In It: Be The Change, Marcia L. Dority Baker

Information Technology Services: Publications

The influence of established women in IT — specifically Florence Hudson and Melissa Woo — encouraged a librarian to apply for a position in Information Technology Services at the University of Nebraska–Lincoln.

A hands-on approach to planning the IT Leadership conference developed a strong collaborative network that also helped grow attendance.

Paying attention to the pros and cons of the 2016 conference guided the planners in modifying their approach to the upcoming October 2017 conference and its focus on diversity and inclusion.

A main goal for future IT Leadership conferences focusing on women and diversity in IT is providing attendees …

Discovery And Characterization Of Small Molecule Rac1 Inhibitors, Jamie L. Arnst, Ashley L. Hein, Margaret A. Taylor, Nick Y. Palermo, Jacob I. Contreras, Yogesh A. Sonawane, Andrw O. Wahl, Michel M. Ouellette, Amarnath Natarajan, Ying Yan

Holland Computing Center: Faculty Publications

Aberrant activation of Rho GTPase Rac1 has been observed in various tumor types, including pancreatic cancer. Rac1 activates multiple signaling pathways that lead to uncontrolled proliferation, invasion and metastasis. Thus, inhibition of Rac1 activity is a viable therapeutic strategy for proliferative disorders such as cancer. Here we identified small molecule inhibitors that target the nucleotide-binding site of Rac1 through in silico screening. Follow up in vitro studies demonstrated that two compounds blocked active Rac1 from binding to its effector PAK1. Fluorescence polarization studies indicate that these compounds target the nucleotide-binding site of Rac1. In cells, both compounds blocked Rac1 binding …

End-To-End Molecular Communication Channels In Cell Metabolism: An Information Theoretic Study, Zahmeeth Sayed Sakkaff, Jennie L. Catlett, Mikaela Cashman, Massimiliano Pierobon, Nicole R. Buan, Myra B. Cohen, Christine A. Kelley

Department of Biochemistry: Faculty Publications

The opportunity to control and fine-tune the behavior of biological cells is a fascinating possibility for many diverse disciplines, ranging from medicine and ecology, to chemical industry and space exploration. While synthetic biology is providing novel tools to reprogram cell behavior from their genetic code, many challenges need to be solved before it can become a true engineering discipline, such as reliability, safety assurance, reproducibility and stability. This paper aims to understand the limits in the controllability of the behavior of a natural (non-engineered) biological cell. In particular, the focus is on cell metabolism, and its natural regulation mechanisms, and …

So What Are You Going To Do With That? The Promises And Pitfalls Of Massive Data Sets, Sigrid Anderson Cordell, Melissa Gomis

University of Nebraska-Lincoln Libraries: Faculty Publications

This article takes as its case study the challenge of data sets for text mining, sources that offer tremendous promise for digital humanities (DH) methodology but present specific challenges for humanities scholars. These text sets raise a range of issues: What skills do you train humanists to have? What is the library’s role in enabling and supporting use of those materials? How do you allocate staff? Who oversees sustainability and data management? By addressing these questions through a specific use case scenario, this article shows how these questions are central to mapping out future directions for a range of library …

Smart Underground Antenna Arrays: A Soil Moisture Adaptive Beamforming Approach, Abdul Salam, Mehmet C. Vuran

School of Computing: Technical Reports

In this paper, a novel framework for underground beamforming using adaptive antenna arrays is presented. Based on the analysis of propagation in wireless underground channel, a theoretical model is developed which uses soil moisture information and feedback mechanism to improve performance wireless underground communications. Array element in soil has been analyzed empirically and impacts of soil type and soil moisture on return loss and resonant frequency are investigated. Beam patterns are investigated to communicate with both underground and above ground devices. Depending on the incident angle, refraction from soil-air interface has the adverse effects in the UG communications. It is …

Wireless Underground Channel Diversity Reception With Multiple Antennas For Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran

School of Computing: Conference and Workshop Papers

Internet of underground things (IOUT) is an emerging paradigm which consists of sensors and communication devices, partly or completely buried underground for real-time soil sensing and monitoring. In this paper, the performance of different modulation schemes in IOUT communications is studied through simulations and experiments. The spatial modularity of direct, lateral, and reflected components of the UG channel is exploited by using multiple antennas. First, it has been shown that bit error rates of $10^{-3}$ can be achieved with normalized delay spreads ($\tau_d$) lower than $0.05$. Evaluations are conducted through the first software-defined radio-based field experiments for UG channel. Moreover, …

Towards Internet Of Underground Things In Smart Lighting: A Statistical Model Of Wireless Underground Channel, Abdul Salam, Mehmet C. Vuran, Suat Irmak

School of Computing: Conference and Workshop Papers

The Internet of Underground Things (IOUT) has many applications in the area of smart lighting. IOUT enables communications in smart lighting through underground (UG) and aboveground (AG) communication channels. In IOUT communications, an in-depth analysis of the wireless underground channel is important to design smart lighting solutions. In this paper, based on the empirical and the statistical analysis, a statistical channel model for the UG channel has been developed. The parameters for the statistical tapped-delay-line model are extracted from the measured power delay profiles (PDP). The PDP of the UG channel is represented by the exponential decay of the lateral, …

Smart Underground Antenna Arrays: A Soil Moisture Adaptive Beamforming Approach, Abdul Salam, Mehmet C. Vuran

School of Computing: Conference and Workshop Papers

Current wireless underground (UG) communication techniques are limited by their achievable distance. In this paper, a novel framework for underground beamforming using adaptive antenna arrays is presented to extend communication distances for practical applications. Based on the analysis of propagation in wireless underground channel, a theoretical model is developed which uses soil moisture information to improve wireless underground communications performance. Array element in soil is analyzed empirically and impacts of soil type and soil moisture on return loss (RL) and resonant frequency are investigated. Accordingly, beam patterns are analyzed to communicate with underground and above ground devices. Depending on the …

Biosimp: Using Software Testing Techniques For Sampling And Inference In Biological Organisms, Mikaela Cashman, Jennie L. Catlett, Myra B. Cohen, Nicole R. Buan, Zahmeeth Sakkaff, Massimiliano Pierobon, Christine A. Kelley

School of Computing: Conference and Workshop Papers

Years of research in software engineering have given us novel ways to reason about, test, and predict the behavior of complex software systems that contain hundreds of thousands of lines of code. Many of these techniques have been inspired by nature such as genetic algorithms, swarm intelligence, and ant colony optimization. In this paper we reverse the direction and present BioSIMP, a process that models and predicts the behavior of biological organisms to aid in the emerging field of systems biology. It utilizes techniques from testing and modeling of highly-configurable software systems. Using both experimental and simulation data we show …

The R Journal (December 2016) 8(2): Complete Issue, The R Foundation

The R Journal

Editorial, Michael Lawrence

Contributed Research Articles

multipleNCC: Inverse Probability Weighting of Nested Case-Control Data, Nathalie C. Støer and Sven Ove Samuelsen

QPot: An R Package for Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, and Karen C. Abbott

Design of the TRONCO BioConductor Package for TRanslational ONCOlogy, Marco Antoniotti, Giulio Caravagna, Luca De Sano, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, and Daniele Ramazzotti

diverse: An R Package to Analyze Diversity in Complex Systems, Miguel R. Guevara, Dominik Hartmann, and Marcelo Mendoza

Simulating Correlated Binary and Multinomial Responses under Marginal Model Specification: …

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.3.2 patched

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

The Bioconductor project provides tools for the analysis and comprehension of high throughput genomic data. Bioconductor 3.4 was released on 18 October, 2016. It is com patible with R 3.3 and consists of 1296 software packages, 309 experiment data packages, and 933 up-to-date annotation packages. The release announcement includes descriptions of 101 new packages, and updated NEWS files for many additional packages. Start using Bioconductor by installing the most recent version of R and evaluating the commands

Mctest: An R Package For Detection Of Collinearity Among Regressors, Muhammad Imdadullah, Muhammad Aslam, Saima Altaf

The R Journal

It is common for linear regression models to be plagued with the problem of multicollinearity when two or more regressors are highly correlated. This problem results in unstable estimates of regression coefficients and causes some serious problems in validation and interpretation of the model. Different diagnostic measures are used to detect multicollinearity among regressors. Many statistical software and R packages provide few diagnostic measures for the judgment of multicollinearity. Most widely used diagnostic measures in these software are: coefficient of determination (R2), variance inflation factor/tolerance limit (VIF/TOL), eigenvalues, condition number (CN) and condition index (CI) etc. In this manuscript, we …

Weighted Distance Based Discriminant Analysis: The R Package Wedibadis, Itziar Irigoien, Francesc Mestres, Concepcion Arenas

The R Journal

The WeDiBaDis package provides a user friendly environment to perform discriminant analysis (supervised classification). WeDiBaDis is an easy to use package addressed to the biological and medical communities, and in general, to researchers interested in applied studies. It can be suitable when the user is interested in the problem of constructing a discriminant rule on the basis of distances between a relatively small number of instances or units of known unbalanced-class membership measured on many (possibly thousands) features of any type. This is a current situation when analyzing genetic biomedical data. This discriminant rule can then be used both, as …

Computing Pareto Frontiers And Database Preferences With The Rpref Package, Patrick Roocks

The R Journal

The concept of Pareto frontiers is well-known in economics. Within the database community there exist many different solutions for the specification and calculation of Pareto frontiers, also called Skyline queries in the database context. Slight generalizations like the combination of the Pareto operator with the lexicographical order have been established under the term database preferences. In this paper we present the rPref package which allows to efficiently deal with these concepts within R. With its help, database preferences can be specified in a very similar way as in a state-of-the-art database management system. Our package provides algorithms for an …

Dcovts: Distance Covariance/Correlation For Time Series, Maria Pitsillou, Konstantinos Fokianos

The R Journal

The distance covariance function is a new measure of dependence between random vectors. We drop the assumption of iid data to introduce distance covariance for time series. The R package dCovTS provides functions that compute and plot distance covariance and correlation functions for both univariate and multivariate time series. Additionally it includes functions for testing serial independence based on distance covariance. This paper describes the theoretical background of distance covariance methodology in time series and discusses in detail the implementation of these methods with the R package dCovTS.

Subgroup Discovery With Evolutionary Fuzzy Systems In R: The Sdefsr Package, Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona, María J. Del Jesus

The R Journal

Subgroup discovery is a data mining task halfway between descriptive and predictive data mining. Nowadays it is very relevant for researchers due to the fact that the knowledge extracted is simple and interesting. For this task, evolutionary fuzzy systems are well suited algorithms because they can find a good trade-off between multiple objectives in large search spaces. In fact, this paper presents the SDEFSR package, which contains all the evolutionary fuzzy systems for subgroup discovery presented throughout the literature. It is a package without dependencies on other software, providing functions with recommended default parameters. In addition, it brings a graphical …

Variants Of Simple Correspondence Analysis, Rosaria Lombardo, Eric J. Beh

The R Journal

This paper presents the R package CAvariants (Lombardo and Beh, 2017). The package performs six variants of correspondence analysis on a two-way contingency table. The main function that shares the same name as the package– CAvariants– allows the user to choose (via a series of input parameters) from six different correspondence analysis procedures. These include the classical approach to (symmetrical) correspondence analysis, singly ordered correspondence analysis, doubly ordered correspondence analysis, non symmetrical correspondence analysis, singly ordered non symmetrical correspondence analysis and doubly ordered non symmetrical correspondence analysis. The code provides the flexibility for constructing either a classical correspondence plot or …

Diverse: An R Package To Analyze Diversity In Complex Systems, Miguel R. Guevara, Dominik Hartmann, Marcelo Mendoza

The R Journal

The package diverse provides an easy-to-use interface to calculate and visualize different aspects of diversity in complex systems. In recent years, an increasing number of research projects in social and interdisciplinary sciences, including fields like innovation studies, scientometrics, economics, and network science have emphasized the role of diversification and sophistication of socioeconomic systems. However, so far no dedicated package exists that covers the needs of these emerging fields and interdisciplinary teams. Most packages about diversity tend to be created according to the demands and terminology of particular areas of natural and biological sciences. The package diverse uses interdisciplinary concepts of …

Design Of The Tronco Bioconductor Package For Translational Oncology, Marco Antoniotti, Giulio Caravagna, Luca De Sano, Alex Graudenzi, Giancarlo Mauri, Bud Mishra, Daniele Ramazzotti

The R Journal

Models of cancer progression provide insights on the order of accumulation of genetic alterations during cancer development. Algorithms to infer such models from the currently available mutational profiles collected from different cancer patients (cross-sectional data) have been defined in the literature since late the 90s. These algorithms differ in the way they extract a graphical model of the events modelling the progression, e.g., somatic mutations or copy-number alterations.

TRONCO is an R package for TRanslational ONcology which provides a series of functions to assist the user in the analysis of cross-sectional genomic data and, in particular, it implements …

Qpot: An R Package For Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, Karen C. Abbott

The R Journal

QPot (pronounced ky oo + p¨ at) is an R package for analyzing two-dimensional systems of stochastic differential equations. It provides users with a wide range of tools to simulate, analyze, and visualize the dynamics of these systems. One of QPot’s key features is the computation of the quasi-potential, an important tool for studying stochastic systems. Quasi-potentials are particularly useful for comparing the relative stabilities of equilibria in systems with alternative stable states. This paper describes QPot’s primary functions, and explains how quasi-potentials can yield insights about the dynamics of stochastic systems. Three worked examples guide users through the application …