Computational Biology Commons^™

A Unified Framework Integrating Parent-Of-Origin Effects For Association Study, Feifei Xiao, Jianzhong Ma, Christopher I. I. Amos

Dartmouth Scholarship

Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting is related to several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we generalize the natural and orthogonal interactions (NOIA) framework to allow for estimation of both main allelic effects and POEs. We develop a statistical (Stat-POE) model that has the orthogonal estimates of parameters including …

Creating A Package In R, Brit Schneiders, Eric Archer

STAR Program Research Presentations

In a time of increasingly efficient technology and data production, scientists are producing data faster than it can be analyzed. Therefore, user accessibility to data analysis is becoming more and more critical. In general, researchers have a set of raw data and want an efficient means to their final analysis. A package serves as that means by creating a set of functions and making them accessible to the user. Often, a user has a small piece of code to run (a single R script, for example), and that script requires the use of certain functions, which are contained in a …

Physiologically-Based Pharmacokinetic Modeling For Predicting Caffeine/Theophylline-Ciprofloxacin Interactions, David M. Ng, Ali Navid

STAR Program Research Presentations

Dynamics of interactions between the drugs caffeine, theophylline, 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 are 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, soft drinks, and energy drinks, are actually drugs that affect the body. Ciprofloxacin is an inhibitor of caffeine and theophylline metabolism; such inhibition …

Rna-Sequencing Applications: Gene Expression Quantification And Methylator Phenotype Identification, Guoshuai Cai

Dissertations and Theses (Open Access)

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status.

Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We …

Transcription Factor Binding Profiles Reveal Cyclic Expression Of Human Protein-Coding Genes And Non-Coding Rnas, Chao Cheng, Matthew Ung, Gavin D. Grant, Michael L. Whitfield

Dartmouth Scholarship

Cell cycle is a complex and highly supervised process that must proceed with regulatory precision to achieve successful cellular division. Despite the wide application, microarray time course experiments have several limitations in identifying cell cycle genes. We thus propose a computational model to predict human cell cycle genes based on transcription factor (TF) binding and regulatory motif information in their promoters. We utilize ENCODE ChIP-seq data and motif information as predictors to discriminate cell cycle against non-cell cycle genes. Our results show that both the trans- TF features and the cis- motif features are predictive of cell cycle genes, and …

A Comprehensive And Integrative Reconstruction Of Evolutionary History For Anomura (Crustacea: Decapoda)., Heather D Bracken-Grissom, Maren E Cannon, Patricia Cabezas, Rodney M Feldmann, Carrie E Schweitzer, Shane T Ahyong, Darryl L Felder, Rafael Lemaitre, Keith A Crandall

Computational Biology Institute

BACKGROUND: The infraorder Anomura has long captivated the attention of evolutionary biologists due to its impressive morphological diversity and ecological adaptations. To date, 2500 extant species have been described but phylogenetic relationships at high taxonomic levels remain unresolved. Here, we reconstruct the evolutionary history-phylogeny, divergence times, character evolution and diversification-of this speciose clade. For this purpose, we sequenced two mitochondrial (16S and 12S) and three nuclear (H3, 18S and 28S) markers for 19 of the 20 extant families, using traditional Sanger and next-generation 454 sequencing methods. Molecular data were combined with 156 morphological characters in order to estimate the largest …

Phage Cluster Relationships Identified Through Single Gene Analysis., Kyle C Smith, Eduardo Castro-Nallar, Joshua Nb Fisher, Donald P Breakwell, Julianne H Grose, Sandra H Burnett

Computational Biology Institute

BACKGROUND: Phylogenetic comparison of bacteriophages requires whole genome approaches such as dotplot analysis, genome pairwise maps, and gene content analysis. Currently mycobacteriophages, a highly studied phage group, are categorized into related clusters based on the comparative analysis of whole genome sequences. With the recent explosion of phage isolation, a simple method for phage cluster prediction would facilitate analysis of crude or complex samples without whole genome isolation and sequencing. The hypothesis of this study was that mycobacteriophage-cluster prediction is possible using comparison of a single, ubiquitous, semi-conserved gene. Tape Measure Protein (TMP) was selected to test the hypothesis because it …

Machine Learning And Genome Annotation: A Match Meant To Be?, Kevin Y. Yip, Chao Cheng, Mark Gerstein

Dartmouth Scholarship

By its very nature, genomics produces large, high-dimensional datasets that are well suited to analysis by machine learning approaches. Here, we explain some key aspects of machine learning that make it useful for genome annotation, with illustrative examples from ENCODE.

Key Genes For Modulating Information Flow Play A Temporal Role As Breast Tumor Coexpression Networks Are Dynamically Rewired By Letrozole, Nadia M. Penrod, Jason H. Moore

Dartmouth Scholarship

Genes do not act in isolation but instead as part of complex regulatory networks. To understand how breast tumors adapt to the presence of the drug letrozole, at the molecular level, it is necessary to consider how the expression levels of genes in these networks change relative to one another. Using transcriptomic data generated from sequential tumor biopsy samples, taken at diagnosis, following 10-14 days and following 90 days of letrozole treatment, and a pairwise partial orrelation statistic, we build temporal gene coexpression networks. We characterize the structure of each network and identify genes that hold prominent positions for maintaining …

Identification Of Genetic Determinants Of Metastasis And Clonal Relationships Between Primary And Metastatic Tumors, Gaurav Singhal

All Theses and Dissertations (ETDs)

No abstract provided.

A Polyglot Approach To Bioinformatics Data Integration: Phylogenetic Analysis Of Hiv-1, Steven Reisman, Catherine Putonti, George K. Thiruvathukal, Konstantin Läufer

Computer Science: Faculty Publications and Other Works

RNA-interference has potential therapeutic use against HIV-1 by targeting highly-functional mRNA sequences that contribute to the virulence of the virus. Empirical work has shown that within cell lines, all of the HIV-1 genes are affected by RNAi-induced gene silencing. While promising, inherent in this treatment is the fact that RNAi sequences must be highly specific. HIV, however, mutates rapidly, leading to the evolution of viral escape mutants. In fact, such strains are under strong selection to include mutations within the targeted region, evading the RNAi therapy and thus increasing the virus’ fitness in the host. Taking a phylogenetic approach, we …

Identification Of Snps Associated With Variola Virus Virulence, Anne Gatewood Hoen, Shea N. Gardner, Jason H. Moore

Dartmouth Scholarship

Background: Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Findings: Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The …

How Long Is A Piece Of Loop?, Yoonjoo Choi, Sumeet Agarwal, Charlotte M. Deane

Dartmouth Scholarship

Loops are irregular structures which connect two secondary structure elements in proteins. They often play important roles in function, including enzyme reactions and ligand binding. Despite their importance, their structure remains difficult to predict. Most protein loop structure prediction methods sample local loop segments and score them. In particular protein loop classifications and database search methods depend heavily on local properties of loops. Here we examine the distance between a loop's end points (span). We find that the distribution of loop span appears to be independent of the number of residues in the loop, in other words the separation between …

A Novel Computational Framework For Transcriptome Analysis With Rna-Seq Data, Yin Hu

Theses and Dissertations--Computer Science

The advance of high-throughput sequencing technologies and their application on mRNA transcriptome sequencing (RNA-seq) have enabled comprehensive and unbiased profiling of the landscape of transcription in a cell. In order to address the current limitation of analyzing accuracy and scalability in transcriptome analysis, a novel computational framework has been developed on large-scale RNA-seq datasets with no dependence on transcript annotations. Directly from raw reads, a probabilistic approach is first applied to infer the best transcript fragment alignments from paired-end reads. Empowered by the identification of alternative splicing modules, this framework then performs precise and efficient differential analysis at automatically detected …

Detection Of Genomic Inversion From Single End Read, Pankaj Ghimire

Master's Theses

Structural Variations (SVs) are genomic rearrangements that include both copy-number variants,such as insertion,deletions, duplications and balanced variants like inversion and translocations. These SVs are getting more attentions for research and investigation because of their role on human phenotype, genetic diseases and genomic rearrangements. Evolution of Next-generation Sequencing has provided golden opportunities to investigate these variants and make their wider and clear spectrum in human genome. This investigation includes identification of type of SVs and their breakpoints at base pair level. For their effective identification and breakpoint resolution, many techniques are devised mainly based on paired end read. With relatively low …

Chapter 11: Genome-Wide Association Studies, William S. Bush, Jason H. Moore

Dartmouth Scholarship

Genome-wide association studies (GWAS) have evolved over the last ten years into a powerful tool for investigating the genetic architecture of human disease. In this work, we review the key concepts underlying GWAS, including the architecture of common diseases, the structure of common human genetic variation, technologies for capturing genetic information, study designs, and the statistical methods used for data analysis. We also look forward to the future beyond GWAS.

Phylogeny And Evolutionary Patterns In The Dwarf Crayfish Subfamily (Decapoda: Cambarellinae), C. Pedraza-Lara, I. Doadrio, J. Breinholt, Keith A. Crandall

Computational Biology Institute

The Dwarf crayfish or Cambarellinae, is a morphologically singular subfamily of decapod crustaceans that contains only one genus, Cambarellus. Its intriguing distribution, along the river basins of the Gulf Coast of United States (Gulf Group) and into Central México (Mexican Group), has until now lacked of satisfactory explanation. This study provides a comprehensive sampling of most of the extant species of Cambarellus and sheds light on its evolutionary history, systematics and biogeography. We tested the impact of Gulf Group versus Mexican Group geography on rates of cladogenesis using a maximum likelihood framework, testing different models of birth/extinction of lineages. We …

Cross-Ontology Multi-Level Association Rule Mining In The Gene Ontology., Prashanti Manda, Seval Ozkan, Hui Wang, Fiona M. Mccarthy, Susan M. Bridges

BCoE Publications

The Gene Ontology (GO) has become the internationally accepted standard for representing function, process, and location aspects of gene products. The wealth of GO annotation data provides a valuable source of implicit knowledge of relationships among these aspects. We describe a new method for association rule mining to discover implicit co-occurrence relationships across the GO sub-ontologies at multiple levels of abstraction. Prior work on association rule mining in the GO has concentrated on mining knowledge at a single level of abstraction and/or between terms from the same sub-ontology. We have developed a bottom-up generalization procedure called Cross-Ontology Data Mining-Level by …

Phylogenetics Links Monster Larva To Deep-Sea Shrimp., Heather D Bracken-Grissom, Darryl L Felder, Nicole L Vollmer, Joel W Martin, Keith A Crandall

Computational Biology Institute

Mid-water plankton collections commonly include bizarre and mysterious developmental stages that differ conspicuously from their adult counterparts in morphology and habitat. Unaware of the existence of planktonic larval stages, early zoologists often misidentified these unique morphologies as independent adult lineages. Many such mistakes have since been corrected by collecting larvae, raising them in the lab, and identifying the adult forms. However, challenges arise when the larva is remarkably rare in nature and relatively inaccessible due to its changing habitats over the course of ontogeny. The mid-water marine species Cerataspis monstrosa (Gray 1828) is an armored crustacean larva whose adult identity …

Physiologically-Based Pharmacokinetic Modeling Of Acetaminophen Metabolism And Toxicity, David M. Ng, Ali Navid

STAR Program Research Presentations

Acetaminophen is a common analgesic and antipyretic. Metabolism of acetaminophen and acetaminophen-induced liver necrosis are predicted using physiologically-based pharmacokinetic (PBPK) modeling. Pharmacokinetic means the model determines where the drug is 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. Acetaminophen is usually safe and effective when taken as recommended, but consumption at higher levels may lead to liver damage. Additionally, other factors such as alcoholic liver disease, smoking, and malnutrition affect the maximum safe dose of acetaminophen.