Systems Biology Commons^™

Understanding Huntington's Disease Using Machine Learning Approaches, Sonali Lokhande

KGI Theses and Dissertations

Huntington’s disease (HD) is a debilitating neurodegenerative disorder with a complex pathophysiology. Despite extensive studies to study the disease, the sequence of events through which mutant Huntingtin (mHtt) protein executes its action still remains elusive. The phenotype of HD is an outcome of numerous processes initiated by the mHtt protein along with other proteins that act as either suppressors or enhancers of the effects of mHtt protein and PolyQ aggregates. Utilizing an integrative systems biology approach, I construct and analyze a Huntington’s disease integrome using human orthologs of protein interactors of wild type and mHtt protein. Analysis of this integrome …

Bioinformatic And Experimental Approaches For Deeper Metaproteomic Characterization Of Complex Environmental Samples, Ramsunder Mahadevan Iyer

Doctoral Dissertations

The coupling of high performance multi-dimensional liquid chromatography and tandem mass spectrometry for characterization of microbial proteins from complex environmental samples has paved the way for a new era in scientific discovery. The field of metaproteomics, which is the study of protein suite of all the organisms in a biological system, has taken a tremendous leap with the introduction of high-throughput proteomics. However, with corresponding increase in sample complexity, novel challenges have been raised with respect to efficient peptide separation via chromatography and bioinformatic analysis of the resulting high throughput data. In this dissertation, various aspects of metaproteomic characterization, including …

Development, Evaluation, And Application Of A Novel Error Correction Method For Next Generation Sequencing Data, Isaac Akogwu

Dissertations

Tremendous evolvement in sequencing technologies and the vast availability of data due to decreasing cost of Next-Generation-Sequencing (NGS) has availed scientists the opportunity to address a wide variety of evolutionary and biological issues. NGS uses massively parallel technology to accelerate the process at the expense of accuracy and read length in comparison to earlier Sanger methods. Therefore, computational limitations exist in how much analysis and information can be gleaned from the data without performing some form of error correction.

Error correction process is laborious and consumes a lot of computational resources. Despite the existence of many NGS data error correction …

Strand-Specific Libraries For High Throughput Rna Sequencing (Rna-Seq) Prepared Without Poly(A) Selection, Zhao Zhang, William E. Theurkauf, Zhiping Weng, Phillip D. Zamore

Zhao Zhang

BACKGROUND: High throughput DNA sequencing technology has enabled quantification of all the RNAs in a cell or tissue, a method widely known as RNA sequencing (RNA-Seq). However, non-coding RNAs such as rRNA are highly abundant and can consume >70% of sequencing reads. A common approach is to extract only polyadenylated mRNA; however, such approaches are blind to RNAs with short or no poly(A) tails, leading to an incomplete view of the transcriptome. Another challenge of preparing RNA-Seq libraries is to preserve the strand information of the RNAs. DESIGN: Here, we describe a procedure for preparing RNA-Seq libraries from 1 to …

Comparison Of The Regulatory Dynamics Of Related Small Gene Regulatory Networks That Control The Response To Cold Shock In Saccharomyces Cerevisiae, Natalie Williams

Honors Thesis

The Dahlquist Lab investigates the global, transcriptional response of Sacchromyces cerevisiae, baker’s yeast, to the environmental stress of cold shock, using DNA microarrays for the wild type strain and strains deleted for a particular regulatory transcription factor. Gene regulatory networks (GRNs) consist of transcription factors (TF), genes, and the regulatory connections between them that control the resulting mRNA and protein expression levels. We use mathematical modeling to determine the dynamics of the GRN controlling the cold shock response to determine the relative influence of each transcription factor in the network. A family of GRNs has been derived from the …

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. …

Total-Evidence Dating Under The Fossilized Birth–Death Process, Chi Zhang, Tanja Stadler, Serena Klopfstein, Tracy A. Heath, Fredrik Ronquist

Tracy Heath

Bayesian total-evidence dating involves the simultaneous analysis of morphological data from the fossil record and morphological and sequence data from recent organisms, and it accommodates the uncertainty in the placement of fossils while dating the phylogenetic tree. Due to the flexibility of the Bayesian approach, total-evidence dating can also incorporate additional sources of information. Here, we take advantage of this and expand the analysis to include information about fossilization and sampling processes. Our work is based on the recently described fossilized birth–death (FBD) process, which has been used to model speciation, extinction, and fossilization rates that can vary over time …

Biosimp: Using Software Testing Techniques For Sampling And Inference In Biological Organisms, Mikaela Cashman, Jennie L. Catlett, Myra B. Cohen, Nicole R. Buan, Zahmeeth Sakkaff, Massimiliano Pierobon, Christine A. Kelley

CSE Conference and Workshop Papers

Years of research in software engineering have given us novel ways to reason about, test, and predict the behavior of complex software systems that contain hundreds of thousands of lines of code. Many of these techniques have been inspired by nature such as genetic algorithms, swarm intelligence, and ant colony optimization. In this paper we reverse the direction and present BioSIMP, a process that models and predicts the behavior of biological organisms to aid in the emerging field of systems biology. It utilizes techniques from testing and modeling of highly-configurable software systems. Using both experimental and simulation data we show …