Bioinformatics Commons^™

Targeting Ph Domain Proteins For Cancer Therapy, Zhi Tan

Dissertations & Theses (Open Access)

Targeted therapy has been one of the most promising treatment options for cancer during the past decade. Discoveries of potent and selective small molecule inhibitors are critical to new and promising targeted therapy. Pleckstrin Homology (PH) domain proteins are one of the biggest protein families in the human proteome. However, no drugs have been achieved to the late development stages, let alone getting to the market. Thus, a deeper understanding of this protein family is required and there is an urgent need to develop novel small molecule compounds targeting these proteins.

Studies of PH domains began around two decades ago …

Comparing Attributional And Relational Similarity As A Means To Identify Clinically Relevant Drug-Gene Relationships, Safa Fathiamini

Dissertations & Theses (Open Access)

In emerging domains, such as precision oncology, knowledge extracted from explicit assertions may be insufficient to identify relationships of interest. One solution to this problem involves drawing inference on the basis of similarity. Computational methods have been developed to estimate the semantic similarity and relatedness between terms and relationships that are distributed across corpora of literature such as Medline abstracts and other forms of human readable text. Most research on distributional similarity has focused on the notion of attributional similarity, which estimates the similarity between entities based on the contexts in which they occur across a large corpus. A relatively …

Ontology-Based Clinical Information Extraction Using Snomed Ct, Jun Li

Dissertations & Theses (Open Access)

Extracting and encoding clinical information captured in unstructured clinical documents with standard medical terminologies is vital to enable secondary use of clinical data from practice. SNOMED CT is the most comprehensive medical ontology with broad types of concepts and detailed relationships and it has been widely used for many clinical applications. However, few studies have investigated the use of SNOMED CT in clinical information extraction.

In this dissertation research, we developed a fine-grained information model based on the SNOMED CT and built novel information extraction systems to recognize clinical entities and identify their relations, as well as to encode them …

Omics Approaches To Uncover Germline And Somatic Variation Underlying Inherited Sarcomagenesis, Justin Wong

Dissertations & Theses (Open Access)

Sarcomas are rare mesenchymal tumors, making up 15% of all childhood and 1% of all adult tumors. They account for a disproportionate share of mortality in young adults, and if left untreated, are highly likely to metastasize. However, sarcoma etiology is poorly understood, and having numerous histological subtypes has complicated elucidation. To better understand factors underlying sarcomagenesis, we leveraged two rare inherited cancer predisposition syndromes, Li-Fraumeni Syndrome (LFS), and LFS-like (LFSL), both with a high incidence of sarcomas. LFS is caused by mutations in the tumor suppressor gene TP53 (p53), but has variable and incomplete penetrance, suggesting additional acquired …

Genomic And Transcriptomic Landscape Of Colorectal Premalignancy, Kyle Chang

Dissertations & Theses (Open Access)

Colorectal cancer (CRC) is the third most commonly diagnosed cancer among men and women in the United States, with 3 to 5 percent of the cases diagnosed in the background of a hereditary form of the disease. Biologically, CRC is divided into two groups: microsatellite instable (MSI) and chromosomally unstable (CIN). Genomic and transcriptomic characterization of CRC has emerged from large-scale studies in recent years due to the advancement of next-generation sequencing technologies. These studies have identified key genes and pathways altered in CRC and provided insights to the discovery of therapeutic targets. Despite the wealth of knowledge acquired in …

Computational Insights Into The Generation Of Chromosomal Copy Number Changes, Yihua Liu

Dissertations & Theses (Open Access)

Deviations from a diploid configuration of the human genome, spanning single genes or entire chromosomes, can have wide-ranging impacts on the variation of human phenotypes, including Mendelian and complex forms of diseases. These chromosomal alterations — such as duplications, deletions or copy-neutral loss-of-heterozygosity — are thus important forms of genetic variation for phenotyping populations of individuals as well as populations of cells. Indeed, copy number variants (CNVs) serve as hallmarks of critical changes in the development of particular diseases such as cancer and thus may be used as biomarkers. These CNVs may be either inherited (transmitted by germ cells, originating …

Investigating The Impact Of Intragenic Dna Methylation On Gene Expression, And The Clinical Implications On Tumor Cells And Associated Stroma, Michael Mcguire

Dissertations & Theses (Open Access)

Investigations into the function of non-promoter DNA methylation have yielded new insights into epigenetic regulation of gene expression. Previous studies have highlighted the importance of distinguishing between DNA methylation in discrete functional regions; however, integrated non-promoter DNA methylation and gene expression analyses across a wide number of tumor types and corresponding normal tissues have not been performed. Through integrated analysis of gene expression and DNA methylation profiles, we uncovered an enrichment of DNA methylation sites within the gene body and 3’UTR in which DNA methylation is strongly positively correlated with gene expression. We examined 32 tumor types and identified 57 …

Using The Literature To Identify Confounders, Scott Malec

Dissertations & Theses (Open Access)

Prior work in causal modeling has focused primarily on learning graph structures and parameters to model data generating processes from observational or experimental data, while the focus of the literature-based discovery paradigm was to identify novel therapeutic hypotheses in publicly available knowledge. The critical contribution of this dissertation is to refashion the literature-based discovery paradigm as a means to populate causal models with relevant covariates to abet causal inference. In particular, this dissertation describes a generalizable framework for mapping from causal propositions in the literature to subgraphs populated by instantiated variables that reflect observational data. The observational data are those …