Bioinformatics Commons^™

Trip13’S Crucial Role In Pancreatic Cancer Progression, Swati Dhasmana, Anupam Dhasmana, Stella Rios, Iris A. Enriquez-Perez, Sheema Khan, Farrukh Afaq, Upender Manne, Murali M. Yallapu, Subhash Chauhan

Research Symposium

Background: Pancreatic cancer, characterized by its high mortality rate, stands as one of the most aggressive cancer forms. The projected surge in pancreatic cancer-related deaths, making it the second leading cause in the United States by 2030, underscores the urgency for effective early screening tools. This study employs data mining methods to scrutinize bioinformatic data surrounding TRIP13. Examining differential expression across various cancers, correlating TRIP13 expression with pancreatic cancer stages, exploring associations with common cancer genes, and analyzing overall survival rates constitute the core investigations. Integrated with molecular biology techniques, the study further quantifies TRIP13 expression in progressive pancreatic cancer …

Cancer/Testis Gene Expression Changes In Metastatic Cancer, Clara M. Mosentine

Dissertations, Master's Theses and Master's Reports

Metastasis is the movement of cancerous cells to new parts of the body, often through the blood or lymph systems. Metastasis is classified as stage IV cancer, a prognosis that is significantly more difficult to effectively treat compared to earlier cancer stages. We are interested in assessing whether expression of Cancer/testis (CT) genes, a class of genes that are predominantly expressed in germ cells while also being abnormally expressed in a large percentage of cancers, is associated with cancer metastasis. Germ cells make up an organism’s reproductive system, such as the testis and ovaries, and exhibit cellular immortality and, in …

Towards More Complete Metagenomic Analyses Through Circularized Genomes And Conjugative Elements, Benjamin R. Joris

Electronic Thesis and Dissertation Repository

Advancements in sequencing technologies have revolutionized biological sciences and led to the emergence of a number of fields of research. One such field of research is metagenomics, which is the study of the genomic content of complex communities of bacteria. The goal of this thesis was to contribute computational methodology that can maximize the data generated in these studies and to apply these protocols human and environmental metagenomic samples.

Standard metagenomic analyses include a step for binning of assembled contigs, which has previously been shown to exclude mobile genetic elements, and I demonstrated that this phenomenon extends to all conjugative …

Alterations Of The Gut Mycobiome In Patients With Ms - A Bioinformatic Approach, Saumya Shah

Honors Scholar Theses

The mycobiome is the fungal component of the gut microbiome and is implicated in several autoimmune diseases. However, its role in multiple sclerosis (MS) has not been studied. We performed descriptive and formal statistical tests using the R language to characterize the gut mycobiome in people with MS (pwMS) and healthy controls. We found that the microbiome composition of multiple sclerosis patients is different from healthy people. The mycobiome had significantly higher alpha diversity and inter-subject variation in pwMS than controls. Additionally, Saccharomyces and Aspergillus were over-represented in pwMS. Different mycobiome profiles, defined as mycotypes, were associated with different bacterial …

Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede

Dissertations & Theses (Open Access)

Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …

Loss-Of-Function Genomic Variants Highlight Potential Therapeutic Targets For Cardiovascular Disease, Jonas B. Nielsen, Oren Rom, Ida Surakka, Sarah E. Graham, Wei Zhou, Tanmoy Roychowdhury, Lars G. Fritsche, Sarah A. Gagliano Taliun, Carlo Sidore, Yuhao Liu, Maiken E. Gabrielsen, Anne Heidi Skogholt, Brooke Wolford, William Overton, Ying Zhao, Jin Chen, He Zhang, Whitney E. Hornsby, Akua Acheampong, Austen Grooms, Amanda Schaefer, Gregory J. M. Zajac, Luis Villacorta, Jifeng Zhang, Ben Brumpton, Mari Løset, Vivek Rai, Pia R. Lundegaard, Morten S. Olesen, Kent D. Taylor, Donna K. Arnett

Epidemiology and Environmental Health Faculty Publications

Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of …

Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim

Open Educational Resources

This material introduces Linux File System structures and demonstrates how to use commands to communicate with the operating system through a Terminal program. Basic program structures and system() function of Perl are discussed. A brief introduction to gene-sequencing terminology and file formats are given.

Designing Computational Biology Workflows With Perl - Part 1, Esma Yildirim

Open Educational Resources

This material introduces the AWS console interface, describes how to create an instance on AWS with the VMI provided, connect to that machine instance using the SSH protocol. Once connected, it requires the students to write a script to enter the data folder, which includes gene-sequencing input files and print the first five line of each file remotely. The same exercise can be applied if the VMI is installed on a local machine using virtualization software (e.g. Oracle VirtualBox). In this case, the Terminal program of the VMI can be used to do the exercise.

A Plant Pathology View Of Signaling: A Computational Study Of Fusarium Oxysporum Kinomes And Downy Mildew Resistance In Sweet Basil, Gregory Deiulio

Doctoral Dissertations

This dissertation is composed of two projects that focus on pathogen and plant signaling within the framework of plant pathology. The first project targets protein kinases within the species complex Fusarium oxysporum based on genomic information and tracks their presence/absence and copy number variation across evolutionary time. We have predicted the kinomes of 19 Ascomycete fungi using the kinase annotating software Kinannote. Among Fusaria, kinases related to the perception of the environment, such as Histidine kinases, are proliferated. Similarly, I observed the expansion of Target of Rapamycin (TOR) kinase that regulates cell growth and development in responding to environmental cues. …

Computational Analysis Of Genomic Variants Affecting Predicted Microrna:Target Interactions In Prostate Cancer., Angélica Paola Hernández Pérez

KGI Theses and Dissertations

Prostate cancer (PCa) is the most common cancer of men in the United States and is third only to lung and colon as a cause of cancer death. Clinical behavior of the disease is variable and the combination of prostate-specific antigen (PSA) screening and Gleason score staging are currently the best available molecular and pathology tools to predict outcomes. Cancer biology research establishes microRNAs (miRNAs) as key molecular components in both normal and pathological states. Thus, elucidating miRNAs perturbed by genomic alterations will expand our understanding of the molecular taxonomy of PCa with the aim to complement current practices in …

Computational Analyses Of Mrna Ribosome Loading In Arabidopsis Thaliana, Joseph Benjamin Ernest

Doctoral Dissertations

Translation of mRNA into protein is a critical step in gene expression, but the principles guiding its regulation at the genome level are not completely understood. Translation can be quantified at a genome scale by measuring the ribosome loading of mRNA—the extent to which mRNA is associated with ribosomes. In this dissertation, I present investigations into how genome-wide ribosome loading is controlled in Arabidopsis thaliana. In chapter 1, I give an overview of regulation of ribosome loading and translation. In chapter 2, I present research demonstrating for the first time that genome-wide ribosome loading in plants is partially controlled by …

Development Of An In Silico Kir Genotyping Algorithm And Its Application To Population And Cancer Immunogenetic Analyses, Howard Rosoff

Dissertations & Theses (Open Access)

Gene content determination and variant calling in the complex KIR genomic region are useful for immune system function analysis, pathogenesis and disease risk factor elucidation, immunotherapy development, evolutionary investigations, and human migration modeling. Sequence-specific oligonucleotide and sequence-specific primer PCR methods are the de facto standards for KIR presence/absence identification, but the current platforms are unsuitable for SNP calling, impractical for KIR typing large cohorts of DNA samples, and inapplicable for typing repositories in which sequence data, but not cells or cell analytes, are available. Alternative typing methods, such as in silico sequence-based typing, can address the problems associated with amplicon-based …

Fastpop: A Rapid Principal Component Derived Method To Infer Intercontinental Ancestry Using Genetic Data, Yafang Li, Jinyoung Byun, Guoshuai Cai, Xiangjun Xiao, Younghun Han, Olivier Cornelis, James E. Dinulos, Joe Dennis, Douglas Easton, Ivan Gorlov, Michael F. Seldin, Christopher I. Amos

Dartmouth Scholarship

Identifying subpopulations within a study and inferring intercontinental ancestry of the samples are important steps in genome wide association studies. Two software packages are widely used in analysis of substructure: Structure and Eigenstrat. Structure assigns each individual to a population by using a Bayesian method with multiple tuning parameters. It requires considerable computational time when dealing with thousands of samples and lacks the ability to create scores that could be used as covariates. Eigenstrat uses a principal component analysis method to model all sources of sampling variation. However, it does not readily provide information directly relevant to ancestral origin; the …

Computational Methods For Biomarker Identification In Complex Disease, Amin Ahmadi Adl

USF Tampa Graduate Theses and Dissertations

In a modern systematic view of biology, cell functions arise from the interaction between molecular components. One of the challenging problems in systems biology with high-throughput measurements is discovering the important components involved in the development and progression of complex diseases, which may serve as biomarkers for accurate predictive modeling and as targets for therapeutic purposes. Due to the non-linearity and heterogeneity of these complex diseases, traditional biomarker identification approaches have had limited success at finding clinically useful biomarkers. In this dissertation we propose novel methods for biomarker identification that explicitly take into account the non-linearity and heterogeneity of complex …

A Unified Framework For The Prioritization Of Variants Of Uncertain Significance In Hereditary Breast And Ovarian Cancer Patients, Natasha G. Caminsky

Electronic Thesis and Dissertation Repository

A significant proportion of hereditary breast and ovarian cancer (HBOC) patients receive uninformative genetic testing results, an issue exacerbated by the overwhelming quantity of variants of uncertain significance identified. This thesis describes a framework where, aside from protein coding changes, information theory (IT)-based sequence analysis identifies and prioritizes pathogenic variants occurring within sequence elements predicted to be recognized by proteins involved in mRNA splicing, transcription, and untranslated region binding and structure. To support the utilization of IT analysis, we established IT-based variant interpretation accuracy by performing a comprehensive review of mutations altering mRNA splicing in rare and common diseases.

Custom …

Integrated Assessment Of Predicted Mhc Binding And Cross-Conservation With Self Reveals Patterns Of Viral Camouflage, Lu He, Anne S. De Groot, Andres H. Gutierrez, William D. Martin, Lenny Moise, Chris Bailey-Kellogg

Dartmouth Scholarship

Immune recognition of foreign proteins by T cells hinges on the formation of a ternary complex sandwiching a constituent peptide of the protein between a major histocompatibility complex (MHC) molecule and a T cell receptor (TCR). Viruses have evolved means of "camouflaging" themselves, avoiding immune recognition by reducing the MHC and/or TCR binding of their constituent peptides. Computer-driven T cell epitope mapping tools have been used to evaluate the degree to which articular viruses have used this means of avoiding immune response, but most such analyses focus on MHC-facing ‘agretopes'. Here we set out a new means of evaluating the …

Development And Integration Of Informatic Tools For Qualitative And Quantitative Characterization Of Proteomic Datasets Generated By Tandem Mass Spectrometry, Rachel Michelle Adams

Doctoral Dissertations

Shotgun proteomic experiments provide qualitative and quantitative analytical information from biological samples ranging in complexity from simple bacterial isolates to higher eukaryotes such as plants and humans and even to communities of microbial organisms. Improvements to instrument performance, sample preparation, and informatic tools are increasing the scope and volume of data that can be analyzed by mass spectrometry (MS). To accommodate for these advances, it is becoming increasingly essential to choose and/or create tools that can not only scale well but also those that make more informed decisions using additional features within the data. Incorporating novel and existing tools into …

Systems Biology Approaches To Probe Gene Regulation In Bacteria, Diogo F. Troggian Veiga

Dissertations & Theses (Open Access)

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb).

First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses …

Gene Ontology Analysis Of Pairwise Genetic Associations In Two Genome-Wide Studies Of Sporadic Als, Nora Chung Kim, Peter C. Andrews, Folkert W. Asselbergs, H Robert Frost, Scott M. Williams, Brent T. Harris, Cynthia Read, Kathleen D. Askland, Jason H. Moore

Dartmouth Scholarship

It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO).

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.

Optimization Algorithms For Functional Deimmunization Of Therapeutic Proteins, Andrew S. Parker, Wei Zheng, Karl E. Griswold, Chris Bailey-Kellogg

Dartmouth Scholarship

To develop protein therapeutics from exogenous sources, it is necessary to mitigate the risks of eliciting an anti-biotherapeutic immune response. A key aspect of the response is the recognition and surface display by antigen-presenting cells of epitopes, short peptide fragments derived from the foreign protein. Thus, developing minimal-epitope variants represents a powerful approach to deimmunizing protein therapeutics. Critically, mutations selected to reduce immunogenicity must not interfere with the protein's therapeutic activity.

Bioconductor: Open Software Development For Computational Biology And Bioinformatics, Robert C. Gentleman, Vincent J. Carey, Douglas J. Bates, Benjamin M. Bolstad, Marcel Dettling, Sandrine Dudoit, Byron Ellis, Laurent Gautier, Yongchao Ge, Jeff Gentry, Kurt Hornik, Torsten Hothorn, Wolfgang Huber, Stefano Iacus, Rafael Irizarry, Friedrich Leisch, Cheng Li, Martin Maechler, Anthony J. Rossini, Guenther Sawitzki, Colin Smith, Gordon K. Smyth, Luke Tierney, Yee Hwa Yang, Jianhua Zhang

Bioconductor Project Working Papers

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have …