Preliminary Analysis Of An Agent-Based Model For A Tick-Borne Disease,
2011
Old Dominion University
Preliminary Analysis Of An Agent-Based Model For A Tick-Borne Disease, Holly Gaff
Biological Sciences Faculty Publications
Ticks have a unique life history including a distinct set of life stages and a single blood meal per life stage. This makes tick-host interactions more complex from a mathematical perspective. In addition, any model of these interactions must involve a significant degree of stochasticity on the individual tick level. In an attempt to quantify these relationships, I have developed an individual-based model of the interactions between ticks and their hosts as well as the transmission of tick-borne disease between the two populations. The results from this model are compared with those from previously published differential equation based population models. …
Blended Biogeography-Based Optimization For Constrained Optimization,
2011
Shaoxing University, Shaoxing, China
Blended Biogeography-Based Optimization For Constrained Optimization, Haiping Ma, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography-based optimization (BBO) is a new evolutionary optimization method that is based on the science of biogeography. We propose two extensions to BBO. First, we propose a blended migration operator. Benchmark results show that blended BBO outperforms standard BBO. Second, we employ blended BBO to solve constrained optimization problems. Constraints are handled by modifying the BBO immigration and emigration procedures. The approach that we use does not require any additional tuning parameters beyond those that are required for unconstrained problems. The constrained blended BBO algorithm is compared with solutions based on a stud genetic algorithm (SGA) and standard particle swarm …
Statistical Properties Of The Integrative Correlation Coefficient: A Measure Of Cross-Study Gene Reproducibility,
2011
Johns Hopkins University
Statistical Properties Of The Integrative Correlation Coefficient: A Measure Of Cross-Study Gene Reproducibility, Leslie Cope, Giovanni Parmigiani
Harvard University Biostatistics Working Paper Series
No abstract provided.
Evolution And Quantitative Comparison Of Genome-Wide Protein Domain Distributions,
2011
University of Indonesia
Evolution And Quantitative Comparison Of Genome-Wide Protein Domain Distributions, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Arli A Parikesit
The metabolic and regulatory capabilities of an organism are implicit in its protein content. This is often hard to estimate, however, due to ascertainment biases inherent in the available genome annotations. Its complement of recognizable functional protein domains and their combinations convey essentially the same information and at the same time are much more readily accessible, although protein domain models trained for one phylogenetic group frequently fail on distantly related sequences. Pooling related domain models based on their GO-annotation in combination with de novo gene prediction methods provides estimates that seem to be less affected by phylogenetic biases. We show …
Linear Methods For Analysis And Quality Control Of Relative Expression Ratios From Quantitative Real-Time Polymerase Chain Reaction Experiments,
2011
College of Saint Benedict/Saint John's University
Linear Methods For Analysis And Quality Control Of Relative Expression Ratios From Quantitative Real-Time Polymerase Chain Reaction Experiments, Robert B. Page, Arnold J. Stromberg
Biology Faculty Publications
Relative expression quantitative real-time polymerase chain reaction (RT-qPCR) experiments are a common means of estimating transcript abundances across biological groups and experimental treatments. One of the most frequently used expression measures that results from such experiments is the relative expression ratio (RE), which describes expression in experimental samples (i.e., RNA isolated from organisms, tissues, and/or cells that were exposed to one or more experimental or nonbaseline condition) in terms of fold change relative to calibrator samples (i.e., RNA isolated from organisms, tissues, and/or cells that were exposed to a control or baseline condition). Over the past decade, several …
Weighted Scores Method For Regression Models With Dependent Data,
2011
Old Dominion University
Weighted Scores Method For Regression Models With Dependent Data, Aristidis K. Nikoloulopoulos, Harry Joe, N. Rao Chaganty
Mathematics & Statistics Faculty Publications
There are copula-based statistical models in the literature for regression with dependent data such as clustered and longitudinal overdispersed counts, for which parameter estimation and inference are straightforward. For situations where the main interest is in the regression and other univariate parameters and not the dependence, we propose a "weighted scores method", which is based on weighting score functions of the univariate margins. The weight matrices are obtained initially fitting a discretized multivariate normal distribution, which admits a wide range of dependence. The general methodology is applied to negative binomial regression models. Asymptotic and small-sample efficiency calculations show that our …
Computational Network Analysis Of The Anatomical And Genetic Organizations In The Mouse Brain,
2011
Old Dominion University
Computational Network Analysis Of The Anatomical And Genetic Organizations In The Mouse Brain, Shuiwang Ji
Computer Science Faculty Publications
Motivation: The mammalian central nervous system (CNS) generates high-level behavior and cognitive functions. Elucidating the anatomical and genetic organizations in the CNS is a key step toward understanding the functional brain circuitry. The CNS contains an enormous number of cell types, each with unique gene expression patterns. Therefore, it is of central importance to capture the spatial expression patterns in the brain. Currently, genome-wide atlas of spatial expression patterns in the mouse brain has been made available, and the data are in the form of aligned 3D data arrays. The sheer volume and complexity of these data pose significant challenges …
Clustering With Exclusion Zones: Genomic Applications,
2010
University of California, San Francisco
Clustering With Exclusion Zones: Genomic Applications, Mark Segal, Yuanyuan Xiao, Fred Huffer
Mark R Segal
Methods for formally evaluating the clustering of events in space or time, notably the scan statistic, have been richly developed and widely applied. In order to utilize the scan statistic and related approaches, it is necessary to know the extent of the spatial or temporal domains wherein the events arise. Implicit in their usage is that these domains have no “holes”—hereafter “exclusion zones”—regions in which events a priori cannot occur. However, in many contexts, this requirement is not met. When the exclusion zones are known, it is straightforward to correct the scan statistic for their occurrence by simply adjusting the …
Evolution Of Domain Co-Occurrences: Some Striking Results,
2010
University of Indonesia
Evolution Of Domain Co-Occurrences: Some Striking Results, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Arli A Parikesit
No abstract provided.
Minimum Description Length Measures Of Evidence For Enrichment,
2010
Ottawa Institute of Systems Biology, Department of Biochemistry, Microbiology, and Immunology, University of Ottawa
Minimum Description Length Measures Of Evidence For Enrichment, Zhenyu Yang, David R. Bickel
COBRA Preprint Series
In order to functionally interpret differentially expressed genes or other discovered features, researchers seek to detect enrichment in the form of overrepresentation of discovered features associated with a biological process. Most enrichment methods treat the p-value as the measure of evidence using a statistical test such as the binomial test, Fisher's exact test or the hypergeometric test. However, the p-value is not interpretable as a measure of evidence apart from adjustments in light of the sample size. As a measure of evidence supporting one hypothesis over the other, the Bayes factor (BF) overcomes this drawback of the p-value but lacks …
Toxicogenomics Analysis Of Non-Model Transcriptomes Using Next-Generation Sequencing And Microarray,
2010
University of Southern Mississippi
Toxicogenomics Analysis Of Non-Model Transcriptomes Using Next-Generation Sequencing And Microarray, Arun Rawat
Dissertations
With the advent of next generation technologies like Roche/454 Life Sciences that require low cost and less time for sequencing will help in providing a workable draft of non-model species genomes. Availability of high throughput microarray technologies for gene expression profiling provides low-cost tools for investigation of highly-integrated responses to various stimuli. These advancements along with bioinformatics processing have led to an increasing number of non-model species having well-annotated transcriptomes. The project focuses on the life cycle of development, functional annotation, and utilization of genomic tools for the avian wildlife species to determine the molecular impacts of exposure to munitions …
Appearance Based Stage Recognition Of Drosophila Embryos,
2010
Western Kentucky University
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 …
Computational Biology,
2010
University of Colorado Denver
Computational Biology, Harvey Greenberg, Allen Holder
Mathematical Sciences Technical Reports (MSTR)
Computational biology is an interdisciplinary field that applies the techniques of computer science, applied mathematics, and statistics to address biological questions. OR is also interdisciplinary and applies the same mathematical and computational sciences, but to decision-making problems. Both focus on developing mathematical models and designing algorithms to solve them. Models in computational biology vary in their biological domain and can range from the interactions of genes and proteins to the relationships among organisms and species.
Dorsal Eye Selector Pannier (Pnr) Suppresses The Eye Fate To Define Dorsal Margin Of The Drosophila Eye,
2010
University of Dayton
Dorsal Eye Selector Pannier (Pnr) Suppresses The Eye Fate To Define Dorsal Margin Of The Drosophila Eye, Sarah M. Oros, Meghana Tare, Madhuri Kango-Singh, Amit Singh
Biology Faculty Publications
Axial patterning is crucial for organogenesis. During Drosophila eye development, dorso-ventral (DV) axis determination is the first lineage restriction event. The eye primordium begins with a default ventral fate, on which the dorsal eye fate is established by expression of the GATA-1 transcription factor pannier (pnr). Earlier, it was suggested that loss of pnr function induces enlargement in the dorsal eye due to ectopic equator formation. Interestingly, we found that in addition to regulating DV patterning, pnr suppresses the eye fate by downregulating the core retinal determination genes eyes absent (eya), sine oculis (so) and dacshund (dac) to define the …
Using The R Package Crlmm For Genotyping And Copy Number Estimation,
2010
Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics
Using The R Package Crlmm For Genotyping And Copy Number Estimation, Robert B. Scharpf, Rafael Irizarry, Walter Ritchie, Benilton Carvalho, Ingo Ruczinski
Johns Hopkins University, Dept. of Biostatistics Working Papers
Genotyping platforms such as Affymetrix can be used to assess genotype-phenotype as well as copy number-phenotype associations at millions of markers. While genotyping algorithms are largely concordant when assessed on HapMap samples, tools to assess copy number changes are more variable and often discordant. One explanation for the discordance is that copy number estimates are susceptible to systematic differences between groups of samples that were processed at different times or by different labs. Analysis algorithms that do not adjust for batch effects are prone to spurious measures of association. The R package crlmm implements a multilevel model that adjusts for …
Sample Size And Statistical Power Considerations In High-Dimensionality Data Settings: A Comparative Study Of Classification Algorithms,
2010
University of Massachusetts - Amherst
Sample Size And Statistical Power Considerations In High-Dimensionality Data Settings: A Comparative Study Of Classification Algorithms, Yu Guo, Armin Garber, Raji Balasubramanian
Raji Balasubramanian
Background: Data generated using ‘omics’ technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of subjects in the study. In this paper, we consider issues relevant in the design of biomedical studies in which the goal is the discovery of a subset of features and an associated algorithm that can predict a binary outcome, such as disease status. We compare the performance of four commonly used classifiers (K-Nearest Neighbors, Prediction Analysis for Microarrays, Random Forests and Support Vector Machines) in high-dimensionality data settings. We evaluate the effects of varying levels of …
Genome Sequence Of The Model Mushroom Schizophyllum Commune,
2010
Sacred Heart University
Genome Sequence Of The Model Mushroom Schizophyllum Commune, Robin A. Ohm, Jan F. De Jong, Luis G. Lugones, Andrea Aerts, Erika Kothe, Jason E. Stajich, Ronald P. De Vries, Eric Record, Anthony Levasseur, Scott E. Baker, Kirk A. Bartholomew, Pedro M. Coutinho, Susann Erdmann, Thomas J. Fowler, Allen C. Gathmen, Vincent Lombard, Bernard Henrissat, Nicole Knabe, Ursula Kues, Walt W. Lily
Biology Faculty Publications
Much remains to be learned about the biology of mushroom-forming fungi, which are an important source of food, secondary metabolites and industrial enzymes. The wood-degrading fungus Schizophyllum commune is both a genetically tractable model for studying mushroom development and a likely source of enzymes capable of efficient degradation of lignocellulosic biomass. Comparative analyses of its 38.5-megabase genome, which encodes 13,210 predicted genes, reveal the species's unique wood-degrading machinery. One-third of the 471 genes predicted to encode transcription factors are differentially expressed during sexual development of S. commune. Whereas inactivation of one of these, fst4, prevented mushroom formation, inactivation of another, …
G-Lattices For An Unrooted Perfect Phylogeny,
2010
Rose-Hulman Institute of Technology
G-Lattices For An Unrooted Perfect Phylogeny, Monica Grigg
Mathematical Sciences Technical Reports (MSTR)
We look at the Pure Parsimony problem and the Perfect Phylogeny Haplotyping problem. From the Pure Parsimony problem we consider structures of genotypes called g-lattices. These structures either provide solutions or give bounds to the pure parsimony problem. In particular, we investigate which of these structures supports an unrooted perfect phylogeny, a condition that adds biological interpretation. By understanding which g-lattices support an unrooted perfect phylogeny, we connect two of the standard biological inference rules used to recreate how genetic diversity propagates across generations.
A Perturbation Method For Inference On Regularized Regression Estimates,
2010
Harvard University
A Perturbation Method For Inference On Regularized Regression Estimates, Jessica Minnier, Lu Tian, Tianxi Cai
Harvard University Biostatistics Working Paper Series
No abstract provided.
The Maximum Clique Problem: Algorithms, Applications, And Implementations,
2010
University of Tennessee, Knoxville
The Maximum Clique Problem: Algorithms, Applications, And Implementations, John David Eblen
Doctoral Dissertations
Computationally hard problems are routinely encountered during the course of solving practical problems. This is commonly dealt with by settling for less than optimal solutions, through the use of heuristics or approximation algorithms. This dissertation examines the alternate possibility of solving such problems exactly, through a detailed study of one particular problem, the maximum clique problem. It discusses algorithms, implementations, and the application of maximum clique results to real-world problems. First, the theoretical roots of the algorithmic method employed are discussed. Then a practical approach is described, which separates out important algorithmic decisions so that the algorithm can be easily …
