Systems Biology Commons^™

A Persistent Homology Framework For Scrna-Seq: Assessing Clustering Robustness And Quantifying Preprocessing And Integration Effects On Topological Features., Jonah Daneshmand

Electronic Theses and Dissertations

As single-cell RNA sequencing (scRNA-seq) data expands, robust methods for integrating diverse datasets are critical. This dissertation applies Persistent Homology (PH), a technique from Topological Data Analysis (TDA), to a collection of scRNA-seq datasets spanning eight tissue types to quantify how data integration affects topological features and biological interpretability. We assessed global topological structure using Betti curves, Euler characteristics, and persistence landscapes across raw, normalized, and integrated data representations. Our analysis revealed a performance inversion: while conventional methods excelled on unintegrated data, high-granularity topological methods, particularly those sensitive to global data structure, became superior after integration. This suggests a synergy …

Computational Frameworks To Unravel The Immune Landscape, Shan He

Dissertations and Theses (Open Access)

Recent advances in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy, face challenges such as resistance and immune-related adverse events, partly due to our limited understanding of the immune signaling pathways. While high- throughput genomic data provide unprecedented resolution into these immune pathways, their full potential is limited by the lack of well-annotated, context-specific immune gene sets. To address this need, I developed a workflow to construct immune gene sets by integrating RNA- seq datasets and performing decomposition. Using this approach, I constructed 28 immune- specific gene sets from 83 bulk RNA-seq datasets and 12 Natural Killer (NK) …

Early Onset Alzheimer’S Disease Markers In Mouse Hippocampus Unveiled By Single-Cell Transcriptomic Analysis Following Cranial Radiotherapy, Tuba Aksoy

Dissertations and Theses (Open Access)

Cranial radiation therapy plays an integral role in the treatment of brain tumors but can lead to progressive cognitive deficits in survivors by mechanisms that are poorly understood. To develop preventive or mitigative strategies, it is crucial to better understand the underlying pathogenesis of radiation-induced cognitive impairments. The study investigated single-cell transcriptomics and DNA methylation changes as potential drivers of persistent cellular dysfunction after radiation exposure, specifically concentrating on the CA1-3 regions of the hippocampus and the prefrontal cortex due to their role in cognitive functions. Thirteen-week-old mice underwent whole-brain radiation at clinically relevant doses. Following whole-brain radiation, an assessment …

Cytokine Activity Estimation And Receptor Abundance Approximation With Multimodal Scrna-Seq/Cite-Seq Data., Azka Javaid

Dartmouth College Ph.D Dissertations

Single-cell RNA-sequencing (scRNA-seq) data enables individual cell resolution quantification of messenger RNA. While revolutionary for revealing key cell type and cell phenotype-specific heterogeneity, scRNA-seq data has important statistical challenges. First, scRNA-seq data is usually more sparse and second, it is more variable than bulk transcriptomics data. Given these challenges, more intuitive and interpretive statistical and computational methods are needed to develop appropriate solutions. Here, we detail the development of three techniques to perform receptor abundance estimation and cytokine activity estimation for scRNA-seq data. While SPECK (Surface Protein abundance Estimation using CKmeans-based clustered thresholding) and STREAK (gene Set Testing-based Receptor abundance …

Methods And Tools To Improve Performance Of Plant Genome Analysis, Drew Ferrell

Theses and Dissertations

Multi -omics data analysis and integration facilitates hypothesis building toward an understanding of genes and pathway responses driven by environments. Methods designed to estimate and analyze gene expression, with regard to treatments or conditions, can be leveraged to understand gene-level responses in the cell. However, genes often interact and signal within larger structures such as pathways and networks. Complex studies guided toward describing dynamic genetic pathways and networks require algorithms or methods designed for inference based on gene interactions and related topologies. Classes of algorithms and methods may be integrated into generalized workflows for comparative genomics studies, as multi -omics …

Exploiting Chemogenetic And Genetic Interactions In Human Cells As An Avenue For New Therapeutic Opportunities, Medina Colic

Dissertations and Theses (Open Access)

The advent of CRISPR technology and its adaptation to the mammalian genome made whole-genome knockout screens possible directly in human cells. Gene knockout answers how essential that gene is for cell fitness and proliferation. Genes showing moderate to severe fitness defects are called essential genes and provide insights into disease-specific candidate therapeutic targets. Additionally, CRISPR offers other applications for genome editing. Two applications this dissertation is based on are 1) combination of gene knockout and drug treatment, which enables the identification of chemogenetic interactions, or gene mutations that enhance or suppress the activity of a drug, and 2) combinatorial editing, …

Investigation Of Proliferation Suppressors In Genetic Fitness Screens, Walter Frank Lenoir Iv

Dissertations and Theses (Open Access)

Innovation of CRISPR gene-editing technology has provided scientists genome manipulation tools that allowed rapid advancement of scientific capabilities and thus improved our ability to systematically study mammalian genetic functional profiles. Genome-wide CRISPR knockout screens conducted in collections of human cell lines can knock out genes at multiple loci, and have provided new insights into functional roles for independent genes. This method has launched massive efforts in looking across genetic backgrounds for context specific genetic vulnerabilities within cancer. Much of the research effort thus far has been spent on optimizing phenotype distinctions between essential, genes required for cell fitness, and non-essential, …

Deciphering The Role Of Human Arylamine N-Acetyltransferase 1 (Nat1) In Breast Cancer Cell Metabolism Using A Systems Biology Approach., Samantha Marie Carlisle

Electronic Theses and Dissertations

Background: Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. NAT1 can additionally hydrolyze acetyl-coenzyme A (acetyl-CoA) in the absence of an arylamine substrate. NAT1 expression varies inter-individually and is elevated in several cancers including estrogen receptor positive (ER+) breast cancers. Additionally, multiple studies have shown the knockdown of NAT1, by both small molecule inhibition and siRNA methods, in breast cancer cells leads to decreased invasive ability and proliferation and decreased anchorage-independent colony formation. However, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear. Additionally, consequences …

Mutations In Braf Are Associated With Higher Levels Of Immune Infiltrates In Microsatellite-Stable Colon Cancer, Jake Rubin, Eduard Porta Parto

GW Research Days 2016 - 2020

While BRAF is among the most well-established oncogenes in human cancers, more recently it has garnered attention for its role in suppressing antitumor immunity, especially in melanoma. Because tumor-infiltrating lymphocyte (TIL) density is strongly prognostic in colorectal cancer (CRC)⁷, we decided to investigate the connection between TIL density and the BRAF-activating V600E mutation in CRC.

We used ESTIMATE to quantify immune infiltrate in samples from the TCGA colon adenocarcinoma (COAD) dataset (n = 216). This is an algorithm that uses the gene-expression signature of 141 immune-related genes to infer the presence of immune cells in the tumor infiltrate. …

Network Analytics For The Mirna Regulome And Mirna-Disease Interactions, Joseph Jayakar Nalluri

Theses and Dissertations

miRNAs are non-coding RNAs of approx. 22 nucleotides in length that inhibit gene expression at the post-transcriptional level. By virtue of this gene regulation mechanism, miRNAs play a critical role in several biological processes and patho-physiological conditions, including cancers. miRNA behavior is a result of a multi-level complex interaction network involving miRNA-mRNA, TF-miRNA-gene, and miRNA-chemical interactions; hence the precise patterns through which a miRNA regulates a certain disease(s) are still elusive. Herein, I have developed an integrative genomics methods/pipeline to (i) build a miRNA regulomics and data analytics repository, (ii) create/model these interactions into networks and use optimization techniques, motif …

Diversity And Distribution Of Diatom Endosymbionts In Amphistegina Spp. (Foraminifera) Based On Molecular And Morphological Techniques, Kwasi H. Barnes

USF Tampa Graduate Theses and Dissertations

Diatoms associated with foraminifers of the genus Amphistegina were assessed using a combination of morphological and molecular techniques. These included: 1) microscopic identification of diatoms cultured from the host, 2) sequencing of portions of the small subunit of the ribosomal RNA gene (18S) and the large subunit of the ribulose-1,5-bisphosphate carboxylase/oxygenase [i.e., RubisCO] gene (rbcL) from DNA extracted directly from the Amphistegina hosts and also from diatoms cultured from these hosts, and 3) denaturing gradient gel electrophoresis (DGGE) profiles of rbcL and internal transcribed spacer 1 (ITS1) PCR amplicons from DNA extracted directly from …

A Pipeline For Creation Of Genome-Scale Metabolic Reconstructions, Shaun W. Norris

Theses and Dissertations

The decreasing costs of next generation sequencing technologies and the increasing speeds at which they work have lead to an abundance of 'omic datasets. The need for tools and methods to analyze, annotate, and model these datasets to better understand biological systems is growing. Here we present a novel software pipeline to reconstruct the metabolic model of an organism in silico starting from its genome sequence and a novel compilation of biological databases to better serve the generation of metabolic models. We validate these methods using five Gardnerella vaginalis strains and compare the gene annotation results to NCBI and the …

Identification Of Yeast Cell Cycle Regulated Genes Based On Genomic Features, Chao Cheng, Yao Fu, Linsheng Shen, Mark Gerstein

Dartmouth Scholarship

Background: Time-course microarray experiments have been widely used to identify cell cycle regulated genes. However, the method is not effective for lowly expressed genes and is sensitive to experimental conditions. To complement microarray experiments, we propose a computational method to predict cell cycle regulated genes based on their genomic features – transcription factor binding and motif profiles.

Results: Through integrating gene-expression data with ChIP-chip binding and putative binding sites of transcription factors, our method shows high accuracy in discriminating yeast cell cycle regulated genes from non-cell cycle regulated ones. We predict 211 novel cell cycle regulated genes. Our model rediscovers …