Computational Biology Commons^™

A Genomic Island In Salmonella Enterica Ssp. Salamae Provides New Insights On The Genealogy Of The Locus Of Enterocyte Effacement., P Scott Chandry, Simon Gladman, Sean C Moore, Torsten Seemann, Keith A Crandall, Narelle Fegan

Computational Biology Institute

The genomic island encoding the locus of enterocyte effacement (LEE) is an important virulence factor of the human pathogenic Escherichia coli. LEE typically encodes a type III secretion system (T3SS) and secreted effectors capable of forming attaching and effacing lesions. Although prominent in the pathogenic E. coli such as serotype O157:H7, LEE has also been detected in Citrobacter rodentium, E. albertii, and although not confirmed, it is likely to also be in Shigella boydii. Previous phylogenetic analysis of LEE indicated the genomic island was evolving through stepwise acquisition of various components. This study describes a new LEE region from two …

In Silico Prediction Of Protein-Protein Interactions Between Cronobacter Sakazakii And Human Host, Sean Held

Theses

The genus Cronobacter accommodates 16 biogroups of the emerging opportunistic pathogen known formerly as Enterobacter sakazakii. Cronobacter are occasional contaminants of milk powder and, consequently, powdered infant formula (PIT). Since it is a pathogen that is transmitted in infant formula it represents a significant health risk to neonates. These bacteria are opportunistic pathogens (can only cause disease when the host's resistance is low) and are linked with life-threatening infections in neonates. Some of the clinical symptoms of Cronohacter infection include necrotizing enterocolitis, bacteremia, and meningitis, with case fatality rates of 50-80% being reported (Healy et al. 2010). Infant formula manufacturers …

Dynamic Herbal Monographs For A Digital World, Niamh O'Brien

Theses

Post analysis of a worldwide survey of Medical Herbalists, 93% of respondents were in favour of an online system which could update monographs dynamically. 63% of respondents suggested that some current monographs are out of date and lack certain practicalities in areas such as : Interactions, Dosage and Safety. Research into gaining optimal responses from surveys led to a 78% response rate. Survey analysis resulted in a modem up-to-date monograph template being created and each of the aforementioned information systems tested against same. Testing involved the generation of XML, HTML, PHP and OWL languages for encoding documents to allow for …

On The Global Stability Of A Generalized Cholera Epidemiological Model, Yuanji Cheng, Jin Wang, Xiuxiang Yang

Mathematics & Statistics Faculty Publications

In this paper, we conduct a careful global stability analysis for a generalized cholera epidemiological model originally proposed in [J. Wang and S. Liao, A generalized cholera model and epidemic/endemic analysis, J. Biol. Dyn. 6 (2012), pp. 568-589]. Cholera is a water-and food-borne infectious disease whose dynamics are complicated by the multiple interactions between the human host, the pathogen, and the environment. Using the geometric approach, we rigorously prove the endemic global stability for the cholera model in three-dimensional (when the pathogen component is a scalar) and four-dimensional (when the pathogen component is a vector) systems. This work unifies the …

Recent Progress In Polymorphism-Based Population Genetic Inference., Jessica Crisci, Yu-Ping Poh, Angela Bean, Alfred Simkin, Jeffrey Jensen

Jessica L Crisci

The recent availability of whole-genome sequencing data affords tremendous power for statistical inference. With this, there has been great interest in the development of polymorphism-based approaches for the estimation of population genetic parameters. These approaches seek to estimate, for example, recently fixed or sweeping beneficial mutations, the rate of recurrent positive selection, the distribution of selection coefficients, and the demographic history of the population. Yet despite estimating similar parameters using similar data sets, results between methodologies are far from consistent. We here summarize the current state of the field, compare existing approaches, and attempt to reconcile emerging discrepancies. We also …

Modeling Protein Expression And Protein Signaling Pathways, Donatello Telesca, Peter Muller, Steven Kornblau, Marc Suchard, Yuan Ji

COBRA Preprint Series

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The …

A Study Of Correlations Between The Definition And Application Of The Gene Ontology, Yuji Mo

Computer and Electronics Engineering: Dissertations, Theses, and Student Research

When using the Gene Ontology (GO), nucleotide and amino acid sequences are annotated by terms in a structured and controlled vocabulary organized into relational graphs. The usage of the vocabulary (GO terms) in the annotation of these sequences may diverge from the relations defined in the ontology. We measure the consistency of the use of GO terms by comparing GO's defined structure to the terms' application. To do this, we first use synthetic data with different characteristics to understand how these characteristics influence the correlation values determined by various similarity measures. Using these results as a baseline, we found that …

Planning Combinatorial Disulfide Cross-Links For Protein Fold Determination, Fei Xiong, Alan M Friedman, Chris Bailey-Kellogg

Dartmouth Scholarship

Fold recognition techniques take advantage of the limited number of overall structural organizations, and have become increasingly effective at identifying the fold of a given target sequence. However, in the absence of sufficient sequence identity, it remains difficult for fold recognition methods to always select the correct model. While a native-like model is often among a pool of highly ranked models, it is not necessarily the highest-ranked one, and the model rankings depend sensitively on the scoring function used. Structure elucidation methods can then be employed to decide among the models based on relatively rapid biochemical/biophysical experiments.

Exploring The Role Of The Solvent In The Denaturation Of A Protein: A Molecular Dynamics Study Of The Dna Binding Domain Of The 434 Repressor, Celia Schiffer, Volker Dötsch, Kurt Wuthrich, Wilfred Van Gunsteren

Celia A. Schiffer

Molecular dynamics simulations of the DNA binding domain of 434 repressor are presented which aim at unraveling the role of solvent in protein denaturation. Four altered solvent models, each mimicking various possible aspects of the addition of a denaturant to the aqueous solvent, were used in the simulations to analyze their effects on the stability of the protein. The solvent was altered by selectively changing the Coulombic interaction between water and protein atoms and between different water molecules. The use of a modified solvent model has the advantage of mimicking the presence of denaturant without having denaturant molecules present in …

Additive Functions In Boolean Models Of Gene Regulatory Network Modules, Christian Darabos, Ferdinando Ferdinando Di Cunto, Marco Tomassini, Jason H. Moore

Dartmouth Scholarship

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome’s evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We …

Transcriptomic Characterization Of A Synergistic Genetic Interaction During Carpel Margin Meristem Development In Arabidopsis Thaliana, April N. Wynn, Elizabeth E. Rueschhoff, Robert G. Franks

Biological Sciences Research

In flowering plants the gynoecium is the female reproductive structure. In Arabidopsis thalianaovules initiate within the developing gynoecium from meristematic tissue located along the margins of the floral carpels. When fertilized the ovules will develop into seeds. SEUSS (SEU) and AINTEGUMENTA (ANT) encode transcriptional regulators that are critical for the proper formation of ovules from the carpel margin meristem (CMM). The synergistic loss of ovule initiation observed in the seu ant double mutant suggests that SEU and ANT share overlapping functions during CMM development. However the molecular mechanism underlying this synergistic interaction is unknown. Using …

Gc-Content Normalization For Rna-Seq Data, Davide Risso, Katja Schwartz, Gavin Sherlock, Sandrine Dudoit

U.C. Berkeley Division of Biostatistics Working Paper Series

Background: Transcriptome sequencing (RNA-Seq) has become the assay of choice for high-throughput studies of gene expression. However, as is the case with microarrays, major technology-related artifacts and biases affect the resulting expression measures. Normalization is therefore essential to ensure accurate inference of expression levels and subsequent analyses thereof.

Results: We focus on biases related to GC-content and demonstrate the existence of strong sample-specific GC-content effects on RNA-Seq read counts, which can substantially bias differential expression analysis. We propose three simple within-lane gene-level GC-content normalization approaches and assess their performance on two different RNA-Seq datasets, involving different species and experimental designs. …

Magnetosome Genes In The Gammaproteobacterium Strain Bw-2, Lucero Rivera, Denis Trubitsyn, Dennis A. Bazylinski

Undergraduate Research Opportunities Program (UROP)

Magnetotactic bacteria (MTB) biomineralize intracellular nanometer-sized, magnetic crystals surrounded by a lipid bilayer membrane known as magnetosomes. These crystals, which consist of magnetite (Fe3O4) or greigite (Fe3S4), causes the cell to align along the geomagnetic field lines as they swim, a phenomenon known as magnetotaxis. Strain BW-2 is a magnetite-producing magnetotactic bacterium isolated from Badwater Basin, Death Valley National Park (California) and is one of only two species of MTB that are known to phylogenetically belong to the Gammaproteobacteria class of the Proteobacteria phylum. The biomineralization of magnetite in magnetotactic bacteria is mediated by a series of genes that include …

Multiple Testing Of Local Maxima For Detection Of Peaks In Chip-Seq Data, Armin Schwartzman, Andrew Jaffe, Yulia Gavrilov, Clifford A. Meyer

Harvard University Biostatistics Working Paper Series

No abstract provided.

The Evolution And Mechanics Of Translational Control In Plants, Justin N. Vaughn

Doctoral Dissertations

The expression of numerous plant mRNAs is attenuated by RNA sequence elements located in the 5' and 3' untranslated regions (UTRs). For example, in plants and many higher eukaryotes, roughly 35% of genes encode mRNAs that contain one or more upstream open reading frames (uORFs) in the 5' UTR. For this dissertation I have analyzed the pattern of conservation of such mRNA sequence elements. In the first set of studies, I have taken a comparative transcriptomics approach to address which RNA sequence elements are conserved between various families of angiosperm plants. Such conservation indicates an element's fundamental importance to plant …

Physiologically-Based Pharmacokinetic Modeling For Predicting Drug-Drug Interactions, David M. Ng, Ali Navid

STAR Program Research Presentations

Dynamics of interactions between the drugs caffeine and ciprofloxacin are predicted using physiologically-based pharmacokinetic (PBPK) modeling. Pharmacokinetic means the model determines where the drugs are distributed in the body over time. Physiologically-based means the anatomy and physiology of the human body is reflected in the structure and functioning of the model. Multiple drugs can interact to increase or decrease their beneficial and/or undesired effects. This is important because some common substances, such as caffeine in coffee and soft drinks, are actually drugs that affect the body. By implementing the model as a computer program, it is relatively straightforward to perform …

A Unified Approach To Non-Negative Matrix Factorization And Probabilistic Latent Semantic Indexing, Karthik Devarajan, Guoli Wang, Nader Ebrahimi

COBRA Preprint Series

Non-negative matrix factorization (NMF) by the multiplicative updates algorithm is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into two matrices, W and H, each with nonnegative entries, V ~ WH. NMF has been shown to have a unique parts-based, sparse representation of the data. The nonnegativity constraints in NMF allow only additive combinations of the data which enables it to learn parts that have distinct physical representations in reality. In the last few years, NMF has been successfully applied in a variety of areas such as natural language processing, information retrieval, image processing, speech recognition …

Evolving Hard Problems: Generating Human Genetics Datasets With A Complex Etiology, Daniel S Himmelstein, Casey S Greene, Jason H Moore

Dartmouth Scholarship

BackgroundA goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models.

Stability Analysis And Application Of A Mathematical Cholera Model, Shu Liao, Jim Wang

Mathematics & Statistics Faculty Publications

In this paper, we conduct a dynamical analysis of the deterministic cholera model proposed in [9]. We study the stability of both the disease-free and endemic equilibria so as to explore the complex epidemic and endemic dynamics of the disease. We demonstrate a real-world application of this model by investigating the recent cholera outbreak in Zimbabwe. Meanwhile, we present numerical simulation results to verify the analytical predictions.

A Bayesian Model Averaging Approach For Observational Gene Expression Studies, Xi Kathy Zhou, Fei Liu, Andrew J. Dannenberg

COBRA Preprint Series

Identifying differentially expressed (DE) genes associated with a sample characteristic is the primary objective of many microarray studies. As more and more studies are carried out with observational rather than well controlled experimental samples, it becomes important to evaluate and properly control the impact of sample heterogeneity on DE gene finding. Typical methods for identifying DE genes require ranking all the genes according to a pre-selected statistic based on a single model for two or more group comparisons, with or without adjustment for other covariates. Such single model approaches unavoidably result in model misspecification, which can lead to increased error …