Relevant bibliographies by topics / Statistical bioinformatics / Dissertations / Theses
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Dissertations / Theses on the topic 'Statistical bioinformatics'

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Published: 20 February 2023

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1

Dijkstra, Martijn. "Bioinformatics for mass spectrometry novel statistical algorithms /." [S.l. : [Groningen : s.n.] ; University Library Groningen] [Host], 2008. http://irs.ub.rug.nl/ppn//.

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2

Nyirongo, Vysaul Bwanamare. "Statistical approaches to protein matching in bioinformatics." Thesis, University of Leeds, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.431995.

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3

Li, Yong-Jun. "The application of statistical physics in bioinformatics /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?PHYS%202003%20LI.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 55-58). Also available in electronic version. Access restricted to campus users.
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4

Kwon, Deukwoo. "Wavelet methods and statistical applications: network security and bioinformatics." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2654.

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Wavelet methods possess versatile properties for statistical applications. We would like to explore the advantages of using wavelets in the analyses in two different research areas. First of all, we develop an integrated tool for online detection of network anomalies. We consider statistical change point detection algorithms, for both local changes in the variance and for jumps detection, and propose modified versions of these algorithms based on moving window techniques. We investigate performances on simulated data and on network traffic data with several superimposed attacks. All detection
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5

Hocking, Toby Dylan. "Learning algorithms and statistical software, with applications to bioinformatics." Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2012. http://tel.archives-ouvertes.fr/tel-00906029.

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Statistical machine learning is a branch of mathematics concerned with developing algorithms for data analysis. This thesis presents new mathematical models and statistical software, and is organized into two parts. In the first part, I present several new algorithms for clustering and segmentation. Clustering and segmentation are a class of techniques that attempt to find structures in data. I discuss the following contributions, with a focus on applications to cancer data from bioinformatics. In the second part, I focus on statistical software contributions which are practical for use in eve
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Andersson, Alfred. "Neural networks for imputation of missing genotype data : An alternative to the classical statistical methods in bioinformatics." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-413635.

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In this project, two different machine learning models were tested in an attempt at imputing missing genotype data from patients on two different panels. As the integrity of the patients had to be protected, initial training was done on data simulated from the 1000 Genomes Project. The first model consisted of two convolutional variational autoencoders and the latent representations of the networks were shuffled to force the networks to find the same patterns in the two datasets. This model was unfortunately unsuccessful at imputing the missing data. The second model was based on a UNet struct
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7

Le, Faucheur Xavier Jean Maurice. "Statistical methods for feature extraction in shape analysis and bioinformatics." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33911.

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The presented research explores two different problems of statistical data analysis. In the first part of this thesis, a method for 3D shape representation, compression and smoothing is presented. First, a technique for encoding non-spherical surfaces using second generation wavelet decomposition is described. Second, a novel model is proposed for wavelet-based surface enhancement. This part of the work aims to develop an efficient algorithm for removing irrelevant and noise-like variations from 3D shapes. Surfaces are encoded using second generation wavelets, and the proposed methodology con
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8

Walter, Klaudia. "Statistical methods for comparative genomics in the field of bioinformatics." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611909.

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9

Li, Yang. "Statistical Methods for Large-Scale Integrative Genomics." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493551.

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In the past 20 years, we have witnessed a significant advance of high-throughput genetic and genomic technologies. With the massively generated genomics data, there is a pressing need for statistical methods that can utilize them to make quantitative inference on substantive scientific questions. My research has been focusing on statistical methods for large-scale integrative genomics. The human genome encodes more than 20,000 genes, while the functions of about 50% (>10,000) genes remains unknown up to date. The determination of the functions of the poorly characterized genes is crucial for
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10

Jung, Min Kyung. "Statistical methods for biological applications." [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3278454.

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Thesis (Ph.D.)--Indiana University, Dept. of Mathematics, 2007.<br>Source: Dissertation Abstracts International, Volume: 68-10, Section: B, page: 6740. Adviser: Elizabeth A. Housworth. Title from dissertation home page (viewed May 20, 2008).
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11

Murie, Carl Eric. "Experimental design and statistical analysis in high throughput screening." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121125.

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High throughput screening (HTS) is a biotechnology that allows researchers to detect the small number of active features (e.g. small molecules, small interfering RNAs) among libraries containing up to hundreds of thousands of features. HTS assays, as with all experimental techniques, are prone to both random error resulting from the inherent variability of biological processes or experimental procedures, and systematic error which can be introduced through any number of known or unknown sources. The effect of both types of error can result in truly inactive features being labeled as active (
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12

Yu, Xiaoqing. "Statistical Methods and Analyses for Next-generation Sequencing Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1403708200.

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13

Golumbeanu, Monica. "Statistical Analysis of PAR-CLIP data." Thesis, KTH, Beräkningsbiologi, CB, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-124347.

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From creation to its degradation, the RNA molecule is the action field of many binding proteins with different roles in regulation and RNA metabolism. Since these proteins are involved in a large number of processes, a variety of diseases are related to abnormalities occurring within the binding mechanisms. One of the experimental methods for detecting the binding sites of these proteins is PAR-CLIP built on the next generation sequencing technology. Due to its size and intrinsic noise, PAR-CLIP data analysis requires appropriate pre-processing and thorough statistical analysis. The present wo
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14

Zhang, Li. "Statistical Methods for Identifying X-linked Genes Associated with Complex Phenotypes." NCSU, 2007. http://www.lib.ncsu.edu/theses/available/etd-10232007-163904/.

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Genetic association studies aim to detect association between one or more genetic polymorphisms and complex traits, which might be some quantitative characteristic or a qualitative attribute of disease. In Chapter 1, we introduce the development of methods for association mapping in the past decades and present the rationale behind our X-linked method development. Family-based association methods have been well developed for autosomes, but unique features of X-linked markers have received little attention. In Chapter 2, we propose a likelihood approach (X-LRT) to estimate genetic risks and tes
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15

Kimura, Takayuki. "RNA-protein structure classifiers incorporated into second-generation statistical potentials." Thesis, San Jose State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10241445.

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<p> Computational modeling of RNA-protein interactions remains an important endeavor. However, exclusively all-atom approaches that model RNA-protein interactions via molecular dynamics are often problematic in their application. One possible alternative is the implementation of hierarchical approaches, first efficiently exploring configurational space with a coarse-grained representation of the RNA and protein. Subsequently, the lowest energy set of such coarse-grained models can be used as scaffolds for all-atom placements, a standard method in modeling protein 3D-structure. However, the coa
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16

Marani, Paola <1970&gt. "From "wet biology" to statistical analysis of structural features with bioinformatics tools." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amsdottorato.unibo.it/689/.

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Many new Escherichia coli outer membrane proteins have recently been identified by proteomics techniques. However, poorly expressed proteins and proteins expressed only under certain conditions may escape detection when wild-type cells are grown under standard conditions. Here, we have taken a complementary approach where candidate outer membrane proteins have been identified by bioinformatics prediction, cloned and overexpressed, and finally localized by cell fractionation experiments. Out of eight predicted outer membrane proteins, we have confirmed the outer membrane localization for five
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17

Nilsson, Roland. "Statistical Feature Selection : With Applications in Life Science." Doctoral thesis, Linköping : Department of Physcis, Chemistry and Biology, Linköping University, 2007. http://www.bibl.liu.se/liupubl/disp/disp2007/tek1090s.pdf.

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18

Moore, Benjamin Luke. "Unravelling higher order chromatin organisation through statistical analysis." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22906.

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Recent technological advances underpinned by high throughput sequencing have given new insights into the three-dimensional structure of mammalian genomes. Chromatin conformation assays have been the critical development in this area, particularly the Hi-C method which ascertains genome-wide patterns of intra and inter-chromosomal contacts. However many open questions remain concerning the functional relevance of such higher order structure, the extent to which it varies, and how it relates to other features of the genomic and epigenomic landscape. Current knowledge of nuclear architecture desc
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19

Kanchinadam, Krishna M. "DataMapX a tool for cross-mapping entities and attributes between bioinformatics databases /." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3135.

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Thesis (M.S.)--George Mason University, 2008.<br>Vita: p. 29. Thesis director: Jennifer Weller. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Bioinformatics. Title from PDF t.p. (viewed July 7, 2008). Includes bibliographical references (p. 28). Also issued in print.
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20

Guturu, Harendra. "Deciphering human gene regulation using computational and statistical methods." Thesis, Stanford University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3581147.

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<p> It is estimated that at least 10-20% of the mammalian genome is dedicated towards regulating the 1-2% of the genome that codes for proteins. This non-coding, regulatory layer is a necessity for the development of complex organisms, but is poorly understood compared to the genetic code used to translate coding DNA into proteins. In this dissertation, I will discuss methods developed to better understand the gene regulatory layer. I begin, in Chapter 1, with a broad overview of gene regulation, motivation for studying it, the state of the art with a historically context and where to look for
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21

Campbell, Kieran. "Probabilistic modelling of genomic trajectories." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:24e6704c-8a7f-4967-9fcd-95d6034eab39.

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The recent advancement of whole-transcriptome gene expression quantification technology - particularly at the single-cell level - has created a wealth of biological data. An increasingly popular unsupervised analysis is to find one dimensional manifolds or trajectories through such data that track the development of some biological process. Such methods may be necessary due to the lack of explicit time series measurements or due to asynchronicity of the biological process at a given time. This thesis aims to recast trajectory inference from high-dimensional "omics" data as a statistical latent
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22

Fernandez, Daniel. "Cell States and Cell Fate: Statistical and Computational Models in (Epi)Genomics." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14226043.

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This dissertation develops and applies several statistical and computational methods to the analysis of Next Generation Sequencing (NGS) data in order to gain a better understanding of our biology. In the rest of the chapter we introduce key concepts in molecular biology, and recent technological developments that help us better understand this complex science, which, in turn, provide the foundation and motivation for the subsequent chapters. In the second chapter we present the problem of estimating gene/isoform expression at the allelic level, and different models to solve this problem. Fir
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23

Sun, Guoli. "Significant distinct branches of hierarchical trees| A framework for statistical analysis and applications to biological data." Thesis, State University of New York at Stony Brook, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3685086.

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<p> One of the most common goals of hierarchical clustering is finding those branches of a tree that form quantifiably distinct data subtypes. Achieving this goal in a statistically meaningful way requires (a) a measure of distinctness of a branch and (b) a test to determine the significance of the observed measure, applicable to all branches and across multiple scales of dissimilarity. </p><p> We formulate a method termed Tree Branches Evaluated Statistically for Tightness (TBEST) for identifying significantly distinct tree branches in hierarchical clusters. For each branch of the tree a me
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24

Allchin, Lorraine Doreen May. "Statistical methods for mapping complex traits." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:65f392ba-1b64-4b00-8871-7cee98809ce1.

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The first section of this thesis addresses the problem of simultaneously identifying multiple loci that are associated with a trait, using a Bayesian Markov Chain Monte Carlo method. It is applicable to both case/control and quantitative data. I present simulations comparing the methods to standard frequentist methods in human case/control and mouse QTL datasets, and show that in the case/control simulations the standard frequentist method out performs my model for all but the highest effect simulations and that for the mouse QTL simulations my method performs as well as the frequentist method
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25

Li, Miaoxin, and 李淼新. "Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43572030.

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26

AMALAPURAPU, SUCHITRA S. "A STATISTICAL ANALYSIS OF AMINO ACID CHANGES IN THE HUMAN GENOME." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1051720394.

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27

Vajdi, Hoojghan Amir. "Application of Graphical Models in Protein-Protein Interactions and Dynamics." Thesis, University of Massachusetts Boston, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10982841.

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<p> Every organism contains a few hundred to thousands of proteins. A protein is made of a sequence of molecular building blocks named amino acids. Amino acids will be referred to as residues. Every protein performs one or more functions in the cell. In order for a protein to do its job, it requires to bind properly to other partner proteins. Many genetic diseases such as cancer are caused by mutations (changes) of specific residues which cause disturbances in the functions of those proteins. The problem of prediction of protein binding site is a crucial topic in computational biology. A prot
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28

Ramasamy, Adaikalavan. "Increasing statistical power and generalizability in genomics microarray research." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:81ccede7-a268-4c7a-9bf8-a2b68634846d.

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The high-throughput technologies developed in the last decade have revolutionized the speed of data accumulation in the life sciences. As a result we have very rich and complex data that holds great promise to solving many complex biological questions. One such technology that is very well established and widespread is DNA microarrays, which allows one to simultaneously measure the expression levels of tens of thousands of genes in a biological tissue. This thesis aims to contribute to the development of statistics that allow the end users to obtain robust and meaningful results from DNA micro
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Li, Miaoxin. "Development of a bioinformatics and statistical framework to integrate biological resources for genome-wide genetic mapping and its applications." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43572030.

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30

Leader, Debbie. "Methods for incorporating biological information into the statistical analysis of gene expression microarray data." Thesis, University of Auckland, 2009. http://hdl.handle.net/2292/5609.

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Microarray technology has made it possible for researchers to simultaneously measure the expression levels of tens of thousands of genes. It is believed that most human diseases and biological phenomena occur through the interaction of groups of genes that are functionally related. To investigate the feasibility of incorporating functional information and/or constraints (based on biological and technical needs) into the classification process two approaches were examined in this thesis. The first of these approaches investigated the effect of incorporating a pre-filter into the gene sel
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31

Wu, Yuhao. "Differential Expression Analysis between Microarray and RNA-seq over Analytical Methods across Statistical Models." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1586452969867803.

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32

Chung, Ren-Hua. "STATISTICAL METHODS FOR FAMILY-BASED ASSOCIATION STUDIES FOR COMPLEX HUMAN DISEASES: SINGLE-LOCUS AND HAPLOTYPE METHODS." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-11062006-134924/.

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Disease-gene fine-mapping is an important task in human genetics. Linkage and association analyses are the two main approaches for exploring disease susceptibility genes. In Chapter 1, we introduce the development of methods for disease-gene mapping in the past decades and present the rationale behind our new method development. Family-based association analyses have provided powerful tools for disease-gene mapping. The Association in the Presence of Linkage test (APL), a family-based association method, can use nuclear families with multiple affected siblings and infer missing parental genoty
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33

Ong, Vy Quoc. "Subgroup Analysis of Patients with Hepatocellular Carcinoma| A Quest for Statistical Algorithms for Tissue Classification Problem." Thesis, California State University, Long Beach, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10840510.

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<p> Hepatocellular carcinoma (HCC) is the most common type of liver cancer. This type of cancer has been observed with prevalence as the third leading cause of death from cancer worldwide and as the ninth leading cause of cancerous mortality in the United States. People with hepatitis B or C are considered to be at high risk for this kind of cancer. Remarkably poor prognostic HCC patients with low survival rates commonly possess intra-hepatic metastases that are either tumor thrombi in the portal vein or intra-hepatic spread. It is uncommon for them to die of extra-hepatic metastases. Therefor
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34

Liu, Tsunglin. "Physics and bioinformatics of RNA." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1141407392.

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35

Chen, Li. "Statistical Machine Learning for Multi-platform Biomedical Data Analysis." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/77188.

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Recent advances in biotechnologies have enabled multiplatform and large-scale quantitative measurements of biomedical events. The need to analyze the produced vast amount of imaging and genomic data stimulates various novel applications of statistical machine learning methods in many areas of biomedical research. The main objective is to assist biomedical investigators to better interpret, analyze, and understand the biomedical questions based on the acquired data. Given the computational challenges imposed by these high-dimensional and complex data, machine learning research finds its new opp
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Coghill, Lyndon M. "Statistical and Comparative Phylogeography of Mexican Freshwater Taxa in Extreme Aquatic Environments." ScholarWorks@UNO, 2013. http://scholarworks.uno.edu/td/1724.

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Phylogeography aims to understand the processes that underlie the distribution of genetic variation within and among closely related species. Although the means by which this goal might be achieved differ considerably from those that spawned the field some thirty years ago, the foundation and conceptual breakthroughs made by Avise are nonetheless the same and are as relevant today as they were two decades ago. Namely, patterns of neutral genetic variation among individuals carry the signature of a species’ demographic past, and the spatial and temporal environmental heterogeneity across a spec
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Sciberras, James. "A SNP-based method for determining the origin of MRSA isolates." Thesis, University of Bath, 2016. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690728.

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The advancements in Whole Genome Sequencing (WGS) have increased the amount of genomic information available for epidemiological analyses. WGS opens many avenues for investigation into the tracking of pathogens, but the rapid advancements in WGS could soon lead to a situation where traditional analytical techniques might become computationally impractical. For example, the traditional method to determine the origin of an isolate is to use phylogenetic analyses. However, phylogenetic analyses become computationally prohibitive with larger datasets and are best for retrospective epidemiology. Th
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Appiah, Simon K. "Space-time statistical analysis of malaria morbidity incidence cases in Ghana: A geostatistical modelling approach." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2014. https://ro.ecu.edu.au/theses/1398.

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Malaria is one of the most prevalent and devastating health problems worldwide. It is a highly endemic disease in Ghana, which poses a major challenge to both the public health and socio-economic development of the country. Major factors accounting for this situation include variability in environmental conditions and lack of prevention services coupled with host of other socio-economic factors. Ghana’s National Malaria Control Programme (NMCP) risk assessment measures have been largely based on household surveys which provided inadequate data for accurate prediction of new incidence cases cou
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Dilthey, Alexander Tilo. "Statistical HLA type imputation from large and heterogeneous datasets." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:1bca18bf-b9d5-4777-b58e-a0dca4c9dbea.

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An individual's Human Leukocyte Antigen (HLA) type is an essential immunogenetic parameter, influencing susceptibility to a variety of autoimmune and infectious diseases, to certain types of cancer and the likelihood of adverse drug reactions. I present and evaluate two models for the accurate statistical determination of HLA types for single-population and multi-population studies, based on SNP genotypes. Importantly, SNP genotypes are already available for many studies, so that the application of the statistical methods presented here does not incur any extra cost besides computing time. HLA
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Su, Zhan. "Statistical methods for the analysis of genetic association studies." Thesis, University of Oxford, 2008. http://ora.ox.ac.uk/objects/uuid:98614f8b-63fe-4fa1-9a24-422216ad14cf.

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One of the main biological goals of recent years is to determine the genes in the human genome that cause disease. Recent technological advances have realised genome-wide association studies, which have uncovered numerous genetic regions implicated with human diseases. The current approach to analysing data from these studies is based on testing association at single SNPs but this is widely accepted as underpowered to detect rare and poorly tagged variants. In this thesis we propose several novel approaches to analysing large-scale association data, which aim to improve upon the power offered
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Latino, Diogo Alexandre Rosa Serra. "Automatic learning for the classification of chemical reactions and in statistical thermodynamics." Doctoral thesis, FCT - UNL, 2008. http://hdl.handle.net/10362/1752.

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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen
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Xu, Qifang. "Statistical Analysis of Biological Interactions from Homologous Proteins." Diss., Temple University Libraries, 2008. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/25686.

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Computer and Information Science<br>Ph.D.<br>Information fusion aims to develop intelligent approaches of integrating information from complementary sources, such that a more comprehensive basis is obtained for data analysis and knowledge discovery. Our Protein Biological Unit (ProtBuD) database is the first database that integrated the biological unit information from the Protein Data Bank (PDB), Protein Quaternary Server (PQS) and Protein Interfaces, Surfaces and Assemblies (PISA) server, and compared the three biological units side-by-side. The statistical analyses show that the inconsisten
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Yip, Wai-Ki. "Statistical Methods for Analyzing DNA Methylation Data and Subpopulation Analysis of Continuous, Binary and Count Data for Clinical Trials." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14226106.

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DNA methylation may represent an important contributor to the missing heritability described in complex trait genetics. However, technology to measure DNA methylation has outpaced statistical methods for analysis. Novel methodologies are required to accommodate this growing volume of DNA methylation data. In this dissertation, I propose two novel methods to analyze DNA methylation data: (1) a new statistic based on spatial location information of DNA methylation sites to detect differentially methylated regions in the genome in case and control studies; and (2) a principal component approach f
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The, Matthew. "Statistical and machine learning methods to analyze large-scale mass spectrometry data." Licentiate thesis, KTH, Genteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-185149.

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As in many other fields, biology is faced with enormous amounts ofdata that contains valuable information that is yet to be extracted. The field of proteomics, the study of proteins, has the luxury of having large repositories containing data from tandem mass-spectrometry experiments, readily accessible for everyone who is interested. At the same time, there is still a lot to discover about proteins as the main actors in cell processes and cell signaling. In this thesis, we explore several methods to extract more information from the available data using methods from statistics and machine lea
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Forster, Thorsten. "Statistical modelling of masked gene regulatory pathway changes across microarray studies of interferon gamma activated macrophages." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9558.

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Interferon gamma (IFN-γ) regulation of macrophages plays an essential role in innate immunity and pathogenicity of viral infections by directing large and small genome-wide changes in the transcriptional program of macrophages. Smaller changes at the transcriptional level are difficult to detect but can have profound biological effects, motivating the hypothesis of this thesis that responses of macrophages to immune activation by IFN-γ include small quantitative changes that are masked by noise but represent meaningful transcriptional systems in pathways against infection. To test this hypothe
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O'Connell, Jared Michael. "Statistical methods for genotype microarray data on large cohorts of individuals." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:4e3328cf-0d8e-4587-b24d-9b59fa220f32.

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Genotype microarrays assay hundreds of thousands of genetic variants on an individual's genome. The availability of this high throughput genotyping capability has transformed the field of genetics over the past decade by enabling thousands of individuals to be rapidly assayed. This has lead to the discovery of hundreds of genetic variants that are associated with disease and other phenotypes in genome wide association studies (GWAS). These data have also brought with them a number of new statistical and computational challenges. This thesis deals with two primary analysis problems involving mi
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Pfeifer, Susanne. "Statistical challenges in the detection of mutation and variation using high throughput sequencing." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:e49ce2fa-aa2c-42d7-bb54-c63e50d14afb.

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The aim of this thesis is to obtain a better understanding of mutation rates within as well as between the genomes of humans and chimpanzees using data generated by high throughput sequencers. I will start with a review of the field and an overview of the technologies and protocols used to generate and analyse high throughput sequencing data. I apply some of the discussed techniques to show that there is evidence of a selective advantage of pathogenic de novo mutations in the Fibroblast Growth Factor Receptor 3 gene in the male germ line of humans. Furthermore, I use some of the methods to gen
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48

Tarazona, Campos Sonia. "Statistical methods for transcriptomics: From microarrays to RNA-seq." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/48485.

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La transcriptómica estudia el nivel de expresión de los genes en distintas condiciones experimentales para tratar de identificar los genes asociados a un fenotipo dado así como las relaciones de regulación entre distintos genes. Los datos ómicos se caracterizan por contener información de miles de variables en una muestra con pocas observaciones. Las tecnologías de alto rendimiento más comunes para medir el nivel de expresión de miles de genes simultáneamente son los microarrays y, más recientemente, la secuenciación de RNA (RNA-seq). Este trabajo de tesis versará sobre la evaluación, adapta
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49

Chen, Xi. "Automatic 13C Chemical Shift Reference Correction of Protein NMR Spectral Data Using Data Mining and Bayesian Statistical Modeling." UKnowledge, 2019. https://uknowledge.uky.edu/biochem_etds/40.

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Nuclear magnetic resonance (NMR) is a highly versatile analytical technique for studying molecular configuration, conformation, and dynamics, especially of biomacromolecules such as proteins. However, due to the intrinsic properties of NMR experiments, results from the NMR instruments require a refencing step before the down-the-line analysis. Poor chemical shift referencing, especially for 13C in protein Nuclear Magnetic Resonance (NMR) experiments, fundamentally limits and even prevents effective study of biomacromolecules via NMR. There is no available method that can rereference carbon che
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50

Vilhelmsson, Sinclair Bella. "Characterization of the Recombination Landscape in Red-Breasted and Taiga Flycatchers." Thesis, Uppsala universitet, Evolutionsbiologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-397376.

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Between closely related species there are genomic regions with a higher level of differentiation compared to the rest of the genome. For a time it was believed that these regions harbored loci important for speciation but it has now been shown that these patterns can arise from other mechanisms, like recombination. The aim of this project was to estimate the recombination landscape for red-breasted flycatcher (Ficedula parva) and taiga flycatcher (F. albicilla) using patterns of linkage disequilibrium. For the analysis, 15 red-breasted and 65 taiga individuals were used. Scaffolds on autosomes
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