Life Sciences 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 …

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 …

Evaluating Reproducibility In Computational Biology Research, Morgan Oneka

Honors Projects

For my Honors Senior Project, I read five research papers in the field of computational biology and attempted to reproduce the results. However, for the most part, this proved a challenge, as many details vital to utilizing relevant software and data had been excluded. Using Geir Kjetil Sandve's paper "Ten Simple Rules for Reproducible Computational Research" as a guide, I discuss how authors of these five papers did and did not obey these rules of reproducibility and how this affected my ability to reproduce their results.

Transcriptome Profiling And Long Non-Coding Rna Identification In Grapevine, Zachary Noel Harris

MSU Graduate Theses

Next-generation sequencing technologies have provided access to vast quantities of nucleic acid sequence data. The resulting wealth of information enables biologists to address complex biological questions in species for which a high-quality well-annotated reference genome sequence has yet to be generated. The cultivated grapevine, Vitis vinifera, has a relatively poorly annotated reference genome. In addition, it is a highly heterozygous species which further hinders the annotation of its genome and the characterization of its transcriptome. Here, I annotated Version 2 of the 12X V. vinifera genome using RNA-seq data derived from the variety ‘Riesling' by employing the most up-to-date computational …

A Longitudinal Cline Characterizes The Genetic Structure Of Human Populations In The Tibetan Plateau, Choongwon Jeong, Benjamin M. Peter, Buddha Basnyat, Maniraj Neupane, Geoff Childs, Sienna Craig, John Novembre, Anna Di Rienzo

Dartmouth Scholarship

Indigenous populations of the Tibetan plateau have attracted much attention for their good performance at extreme high altitude. Most genetic studies of Tibetan adaptations have used genetic variation data at the genome scale, while genetic inferences about their de- mography and population structure are largely based on uniparental markers. To provide genome-wide information on population structure, we analyzed new and published data of 338 individuals from indigenous populations across the plateau in conjunction with world- wide genetic variation data. We found a clear signal of genetic stratification across the east- west axis within Tibetan samples. Samples from more eastern locations …

K-Shell Decomposition Reveals Structural Properties Of The Gene Coexpression Network Forneurodevelopment, Abdullah Ercüment Çi̇çek

Turkish Journal of Biology

Neurodevelopment is a dynamic and complex process, which involves interactions of thousands of genes. Understanding the mechanisms of brain development is important for uncovering the genetic architectures of neurodevelopmental disorders such as autism spectrum disorder and intellectual disability. The BrainSpan dataset is an important resource for studying the transcriptional mechanisms governing neurodevelopment. It contains RNA-seq and microarray data for 13 developmental periods in 8?16 brain regions. Various important studies used this dataset, in particular to generate gene coexpression networks. The topology of the BrainSpan gene coexpression network yielded various important gene clusters, which are found to play key roles in …

Winner's Curse Correction And Variable Thresholding Improve Performance Of Polygenic Risk Modeling Based On Genome-Wide Association Study Summary-Level Data, Jianxin Shi, Ju-Hyun Park, Jubao Duan, Sonja T. Berndt, Winton Moy, Kai Yu, Lei Song, William Wheeler, Xing Hua, Debra Silverman, Montserrat Garcia-Closas, Chao Agnes Hsiung, Jonine D. Figueroa, Victoria K. Cortessis, Nuria Malats, Margaret R. Karagas

Dartmouth Scholarship

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner’s-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied …

Characterizing And Modeling Antibiotic Resistance Dynamics In Diverse Microbial Communities, Molly Krisann Gibson

Arts & Sciences Electronic Theses and Dissertations

Complex microbial communities colonize every habitat investigated to date, including soil, animals, water, and humans, as well as the structures we live in. It has been hypothesized that there is network of exchange allowing both bacterial organisms and functions to seamlessly move between and within these environments. These microbial communities often serve essential and beneficial functions for the host organism or environment. This is particularly evident in the human gut, where microbial communities consistently provide a set of services to its human host, including protecting against enteric pathogens, liberating nutrients from food, and signaling immune system regulation. However, these communities …

Molecular And Computational Methods For Cellular State Control, Drew Groves Michael

Arts & Sciences Electronic Theses and Dissertations

The control of cellular state has many promising applications, including stem cell biology and

regenerative medicine, biofuel production, and gene therapy. This dissertation demonstrates a

comprehensive approach to cellular state control at the transcriptional level. We introduce a

novel algorithm, NetSurgeon, which utilizes genome-wide gene regulatory networks to identify

interventions that will force a cell toward a desired expression state. Following extensive in

silico validation, we applied NetSurgeon to S. cerevisiae biofuel production, generating

interventions designed to promote a fermentative state during xylose catabolism. Our selected

interventions successfully promoted a fermentative transcriptional state and generated strains

with higher xylose import …

Design, Assessment, And In Vivo Evaluation Of A Computational Model Illustrating The Role Of Cav1 In Cd4+ T-Lymphocytes, Brittany D. Conroy, Tyler A. Herek, Timothy D. Shew, Matthew Latner, Joshua J. Larson, Laura Allen, Paul H. Davis, Tomáš Helikar, Christine E. Cutucache

Biology Faculty Publications

Caveolin-1 (CAV1) is a vital scaffold protein heterogeneously expressed in both healthy and malignant tissue. We focus on the role of CAV1 when overexpressed in T-cell leukemia. Previously, we have shown that CAV1 is involved in cell-to-cell communication, cellular proliferation, and immune synapse formation; however, the molecular mechanisms have not been elucidated. We hypothesize that the role of CAV1 in immune synapse formation contributes to immune regulation during leukemic progression, thereby warranting studies of the role of CAV1 in CD4⁺ T-cells in relation to antigen-presenting cells. To address this need, we developed a computational model of a CD4^{+ …}

Phenotypic Robustness And The Assortativity Signature Of Human Transcription Factor Networks, Dov A. Pechenick, Joshua L. Payne, Jason H. Moore

Dartmouth Scholarship

Many developmental, physiological, and behavioral processes depend on the precise expression of genes in space and time. Such spatiotemporal gene expression phenotypes arise from the binding of sequence-specific transcription factors (TFs) to DNA, and from the regulation of nearby genes that such binding causes. These nearby genes may themselves encode TFs, giving rise to a transcription factor network (TFN), wherein nodes represent TFs and directed edges denote regulatory interactions between TFs. Computational studies have linked several topological properties of TFNs - such as their degree distribution - with the robustness of a TFN's gene expression phenotype to genetic and environmental …

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.

Biological Computation, Melanie Mitchell

Computer Science Faculty Publications and Presentations

In this article, the term biological computation refers to the proposal that living organisms themselves perform computations, and, more specifically, that the abstract ideas of information and computation may be key to understanding biology in a more unified manner. It is important to point out that the study of biological computation is typically not the focus of the field of computational biology, which applies computing tools to the solution of specific biological problems. Likewise, biological computation is distinct from the field of biologically-inspired computing, which borrows ideas from biological systems such as the brain, insect colonies, and the immune system …

A Proposed Syntax For Minimotif Semantics, Version 1., Jay Vyas, Ronald J. Nowling, Mark W. Maciejewski, Sanguthevar Rajasekaran, Michael R. Gryk, Martin R. Schiller

Life Sciences Faculty Research

BACKGROUND:

One of the most important developments in bioinformatics over the past few decades has been the observation that short linear peptide sequences (minimotifs) mediate many classes of cellular functions such as protein-protein interactions, molecular trafficking and post-translational modifications. As both the creators and curators of a database which catalogues minimotifs, Minimotif Miner, the authors have a unique perspective on the commonalities of the many functional roles of minimotifs. There is an obvious usefulness in standardizing functional annotations both in allowing for the facile exchange of data between various bioinformatics resources, as well as the internal clustering of sets of …

Bioinformatics Study Of Mammalian Mrna Polydenylation, Haibo Zhang

Dissertations

Messenger RNA polyadenylation is one of the key post-transcriptional events in mammalian cells, which have influences on many aspects of mRNA metabolism. Several human diseases have been shown to associate with abnormal polyadenylation, highlighting the importance of this process. The availability of the complete sequence of human and mouse genomes, together with their gene expression data provides valuable resources to study mRNA polyadenylation on a system level. This dissertation addresses the following issues of mammalian mRNA polyadenylation through bioinformatics approaches: (1) the extensive documentation of several key aspects of polyadenylation sites in humans and mice on a genomic level; (2) …

The Subsystems Approach To Genome Annotation And Its Use In The Project To Annotate 1000 Genomes, Ross Overbeek, Tadhg Begley, Ralph M. Butler, Jomuna V. Choudhuri, Han-Yu Chuang, Matthew Cohoon, Valérie De Crécy-Lagard, Naryttza Diaz, Terry Disz, Robert Edwards, Michael Fonstein, Ed D. Frank, Svetlana Gerdes, Elizabeth M. Glass, Alexander Goesmann, Andrew Hanson, Dirk Iwata-Reuyl, Roy Jensen, Neema Jamshidi, Lutz Krause, Michael Kubal, Niels Larsen, Burkhard Linke, Alice C. Mchardy, Folker Meyer, Heiko Neuweger, Gary Olsen, Robert Olson, Andrei Osterman, Vasiliy Portnoy, Gordon D. Pusch, Dmitry A. Rodionov, Christian Rückert, Jason Steiner, Rick Stevens, Ines Thiele, Olga Vassieva, Yuzhen Ye, Olga Zagnitko, Veronika Vonstein

Chemistry Faculty Publications and Presentations

The release of the 1000^th complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high through put annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by …