Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 384 for “"sequencing data"”.
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Optimal clustering techniques for metagenomic sequencing data
Metagenomic sequencing techniques have made it possible to determine the composition of bacterial microbiota of the human body. Clustering algorithms have been used to search for core microbiota types in the vagina, but results have been inconsistent, possibly due to methodological differences. We …
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Variant Detection Using Next Generation Sequencing Data
… development of cost effective next generation sequencing (NGS) technologies, it has become possible to identify novel variants with high resolutions and to identify some copy neutral variants such as inversions, which cannot be detected using microarray based technologies. However, enormous …
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Error Correction in Next Generation DNA Sequencing Data
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 …
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Improving genome assembly by identifying reliable sequencing data
… ous sub-sequence of the genome assembled from sequencing reads. Scaffolding attempts to construct a linear sequence of contigs (with possible gaps in between) using paired reads (two reads whose distance on the genome is approximately known). In this the- sis I will present a new …
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Bayesian Spatial Analysis of High Throughput Sequencing Data
… the development and wide use of high-throughput sequencing data in biology. The recent advancement of RNA Sequencing (RNA-Seq) coupled with other molecular technologies such as methylated RNA immunoprecipitation (MeRIP) and spatial barcoding has delivered more specialized platform to investigate …
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Resolving developmental dynamics using single-cell sequencing data
… in disease. Over the past decade, single-cell sequencing has become one of the key technologies to generate high resolution in vivo snapshots to study developmental trajectories. After giving an overview of the current state of single cell technologies and computational methods, I continue with …
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Estimating telomere length from whole genome sequencing data
… as well as their applications to whole genome sequencing (WGS) data. Telomerecat is a tool for estimating telomere length from WGS data. The strength of Telomerecat lies in its applicability. This applicability is due to a number of advantages over previous attempts to estimate telomere length …
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Quantifying expression variability in single-cell RNA sequencing data
… reported. The development of single-cell RNA sequencing technologies introduced powerful tools to investigate transcriptional differences between individual cells, therefore allowing the in-depth characterisation of expression variability. In this thesis, I computationally analysed single-cell …
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Computational methods for the analysis of next generation sequencing data
Recently, next generation sequencing (NGS) technology has emerged as a powerful approach and dramatically transformed biomedical research in an unprecedented scale. NGS is expected to replace the traditional hybridization-based microarray technology because of its affordable cost and high digital …
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Measuring ongoing chromosomal instability in single-cell DNA sequencing data
… cell phylogenies. Based only on single-cell DNA sequencing information, scAbsolute achieves accurate and unbiased measurement of single-cell ploidy and replication status, including whole-genome doublings. We demonstrate scAbsolute’s capabilities using experimental cell multiplets, a FUCCI cell …
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Methods for Dissecting High Dimensional Single Cell RNA Sequencing Data
… being described in 2009 [ 1], single cell RNA sequencing (scRNA-seq) has rapidly advanced into a staple for interrogating cellular identity in heterogeneous populations. Researchers routinely capture transcriptome-wide snapshots of thousands or even millions of individual cells. From these …
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Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis
… biology currently faces challenges in a big data world with thousands of data samples across multiple disease types including cancer. The challenging problem is how to extract biologically meaningful information from large-scale genomic data. Next-generation Sequencing (NGS) can now produce …
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Error Correction and de novo Genome Assembly of DNA Sequencing Data
… sciences. Current technologies are capable of sequencing short pieces of DNA with very high quality. These short pieces of DNA determint the sequence of bases in the genome of any species. This information is key in understanding many of the aspects of how life functions. The accuracy of …
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Novel Techniques for Single-cell RNA Sequencing Data Imputation and Clustering
… of the major challenges in analyzing scRNA-seq data is the prevalence of dropouts, which are instances where gene expression is not detected despite being present in the cell. Dropouts occur due to technical limitations and can introduce excessive noise into the data, obscuring the true …
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Identifying biological pathomechanisms of TTN-affected myopathies using RNA-Sequencing data
… genotype-phenotype corelations. RNA-sequencing emerges as a valuable technique for analysing transcriptomic data and exploring gene expression profiles of patient and control samples. To elucidate common pathomechanisms in titinopathies, including adult tibial muscular dystrophy (TMD) …
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Simultaneous SNV calling and Phylogenetic Inference for Single-cell Sequencing Data
Single-cell sequencing provides a powerful approach for elucidating intratumor heterogeneity by resolving cell-to-cell variability. However, it also poses additional challenges including elevated error rates, allelic dropout, and non-uniform coverage. Variant calling in this context is the task of …
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Cancer risk prediction with next generation sequencing data using machine learning
… use of computational biology for next generation sequencing (NGS) analysis is rapidly increasing in genomics research. However, the effectiveness of NGS data to predict disease abundance is yet unclear. This research investigates the problem in the whole exome NGS data of the chronic lymphocytic …
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Navigating through the uncertainty of genotyping-by-sequencing data in polyploids
The development of genotyping-by-sequencing (GBS) methods has facilitated genomics studies in non-model species, including polyploids. Variant and genotype calling methods have been established for autopolyploids but for a species with a complex genome, such as sugarcane, the level of uncertainty …
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Comprehensive evaluation of error correction methods for high-throughput sequencing data
The advent of DNA and RNA sequencing has significantly revolutionized the study of genomics and molecular biology. Development of high-throughput sequencing technologies have brought about a quick and cheaper way to sequence genomes. Different technologies use different underlying methods for …
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