Physical Sciences and Mathematics Commons^™

Decoy-Target Database Strategy And False Discovery Rate Analysis For Glycan Identification, Xiaoou Li

Electronic Thesis and Dissertation Repository

In recent years, the technology of glycopeptide sequencing through MS/MS mass spectrometry data has achieved remarkable progress. Various software tools have been developed and widely used for protein identification. Estimation of false discovery rate (FDR) has become an essential method for evaluating the performance of glycopeptide scoring algorithms. The target-decoy strategy, which involves constructing decoy databases, is currently the most popular utilized method for FDR calculation. In this study, we applied various decoy construction algorithms to generate decoy glycan databases and proposed a novel approach to calculate the FDR by using the EM algorithm and mixture model.

Computational Methods For Predicting Protein-Protein Interactions And Binding Sites, Yiwei Li

Electronic Thesis and Dissertation Repository

Proteins are essential to organisms and participate in virtually every process within cells. Quite often, they keep the cells functioning by interacting with other proteins. This process is called protein-protein interaction (PPI). The bonding amino acid residues during the process of protein-protein interactions are called PPI binding sites. Identifying PPIs and PPI binding sites are fundamental problems in system biology.

Experimental methods for solving these two problems are slow and expensive. Therefore, great efforts are being made towards increasing the performance of computational methods.

We present DELPHI, a deep learning based program for PPI site prediction and SPRINT, an algorithmic …

Machine Learning With Digital Signal Processing For Rapid And Accurate Alignment-Free Genome Analysis: From Methodological Design To A Covid-19 Case Study, Gurjit Singh Randhawa

Electronic Thesis and Dissertation Repository

In the field of bioinformatics, taxonomic classification is the scientific practice of identifying, naming, and grouping of organisms based on their similarities and differences. The problem of taxonomic classification is of immense importance considering that nearly 86% of existing species on Earth and 91% of marine species remain unclassified. Due to the magnitude of the datasets, the need exists for an approach and software tool that is scalable enough to handle large datasets and can be used for rapid sequence comparison and analysis. We propose ML-DSP, a stand-alone alignment-free software tool that uses Machine Learning and Digital Signal Processing to …

Computational Modelling Of Human Transcriptional Regulation By An Information Theory-Based Approach, Ruipeng Lu

Electronic Thesis and Dissertation Repository

ChIP-seq experiments can identify the genome-wide binding site motifs of a transcription factor (TF) and determine its sequence specificity. Multiple algorithms were developed to derive TF binding site (TFBS) motifs from ChIP-seq data, including the entropy minimization-based Bipad that can derive both contiguous and bipartite motifs. Prior studies applying these algorithms to ChIP-seq data only analyzed a small number of top peaks with the highest signal strengths, biasing their resultant position weight matrices (PWMs) towards consensus-like, strong binding sites; nor did they derive bipartite motifs, disabling the accurate modelling of binding behavior of dimeric TFs.

This thesis presents a novel …

Nbpmf: Novel Network-Based Inference Methods For Peptide Mass Fingerprinting, Zhewei Liang

Electronic Thesis and Dissertation Repository

Proteins are large, complex molecules that perform a vast array of functions in every living cell. A proteome is a set of proteins produced in an organism, and proteomics is the large-scale study of proteomes. Several high-throughput technologies have been developed in proteomics, where the most commonly applied are mass spectrometry (MS) based approaches. MS is an analytical technique for determining the composition of a sample. Recently it has become a primary tool for protein identification, quantification, and post translational modification (PTM) characterization in proteomics research. There are usually two different ways to identify proteins: top-down and bottom-up. Top-down approaches …

Signet: A Neural Network Architecture For Predicting Protein-Protein Interactions, Muhammad S. Ahmed

Electronic Thesis and Dissertation Repository

The study of protein-protein interactions (PPI) is critically important within the field of Molecular Biology, as proteins facilitate key organismal functions including the maintenance of both cellular structure and function. Current experimental methods for elucidating PPIs are greatly hindered by large operating costs, lengthy wait times, as well as low accuracy. The recent development of computational PPI predicting techniques has worked to address many of these issues. Despite this, many of these methods utilize over-engineered features and naive learning algorithms. With the recent advances in Machine Learning and Artificial Intelligence, we attempt to view this problem through a novel, deep …

Algorithms For Glycan Structure Identification With Tandem Mass Spectrometry, Weiping Sun

Electronic Thesis and Dissertation Repository

Glycosylation is a frequently observed post-translational modification (PTM) of proteins. It has been estimated over half of eukaryotic proteins in nature are glycoproteins. Glycoprotein analysis plays a vital role in drug preparation. Thus, characterization of glycans that are linked to proteins has become necessary in glycoproteomics. Mass spectrometry has become an effective analytical technique for glycoproteomics analysis because of its high throughput and sensitivity. The large amount of spectral data collected in a mass spectrometry experiment makes manual interpretation impossible and requires effective computational approaches for automated analysis. Different algorithmic solutions have been proposed to address the challenges in glycoproteomics …

Evolution Of Mobile Promoters In Prokaryotic Genomes., Mahnaz Rabbani

Electronic Thesis and Dissertation Repository

Mobile genetic elements are important factors in evolution, and greatly influence the structure of genomes, facilitating the development of new adaptive characteristics. The dynamics of these mobile elements can be described using various mathematical and statistical models. In this thesis, we focus on a specific category of mobile genetic elements, i.e. mobile promoters, which are mobile regions of DNA that initiate the transcription of genes. We present a class of mathematical models for the evolution of mobile promoters in prokaryotic genomes, based on data obtained from available sequenced genomes. Our novel location-based model incorporates two biologically meaningful regions of the …

Algorithms For Peptide Identification From Mixture Tandem Mass Spectra, Yi Liu

Electronic Thesis and Dissertation Repository

The large amount of data collected in an mass spectrometry experiment requires effective computational approaches for the automated analysis of those data. Though extensive research has been conducted for such purpose by the proteomics community, there are still remaining challenges, among which, one particular challenge is that the identification rate of the MS/MS spectra collected is rather low. One significant reason that contributes to this situation is the frequently observed mixture spectra, which result from the concurrent fragmentation of multiple precursors in a single MS/MS spectrum. However, nearly all the mainstream computational methods still take the assumption that the acquired …

Oligonucleotide Design For Whole Genome Tiling Arrays, Qin Dong

Electronic Thesis and Dissertation Repository

Oligonucleotides are short, single-stranded fragments of DNA or RNA, designed to readily bind with a unique part in the target sequence. They have many important applications including PCR (polymerase chain reaction) amplification, microarrays, or FISH (fluorescence in situ hybridization) probes. While traditional microarrays are commonly used for measuring gene expression levels by probing for sequences of known and predicted genes, high-density, whole genome tiling arrays probe intensively for sequences that are known to exist in a contiguous region. Current programs for designing oligonucleotides for tiling arrays are not able to produce results that are close to optimal since they allow …

Modeling Leafhopper Populations And Their Role In Transmitting Plant Diseases., Ji Ruan

Electronic Thesis and Dissertation Repository

This M.Sc. thesis focuses on the interactions between crops and leafhoppers.

Firstly, a general delay differential equations system is proposed, based on the infection age structure, to investigate disease dynamics when disease latencies are considered. To further the understanding on the subject, a specific model is then introduced. The basic reproduction numbers $\cR_0$ and $\cR_1$ are identified and their threshold properties are discussed. When $\cR_0 < 1$, the insect-free equilibrium is globally asymptotically stable. When $\cR_0 > 1$ and $\cR_1 < 1$, the disease-free equilibrium exists and is locally asymptotically stable. When $\cR_1>1$, the disease will persist.

Secondly, we derive another general delay differential equations system to examine how different life stages of leafhoppers affect crops. The basic reproduction numbers $\cR_0$ is determined: when …

Error Correction In Next Generation Dna Sequencing Data, Michael Z. Molnar

Electronic Thesis and Dissertation Repository

Motivation: High throughput Next Generation Sequencing (NGS) technologies can sequence the genome of a species quickly and cheaply. Errors that are introduced by NGS technologies limit the full potential of the applications that rely on their data. Current techniques used to correct these errors are not sufficient, and a more efficient and accurate program is needed to correct errors.

Results: We have designed and implemented RACER (Rapid Accurate Correction of Errors in Reads), an error correction program that targets the Illumina genome sequencer, which is currently the dominant NGS technology. RACER combines advanced data structures with an intricate analysis of …