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Dissertations / Theses on the topic 'Genetic data'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Qiao, Dandi. "Statistical Approaches for Next-Generation Sequencing Data." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10689.

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During the last two decades, genotyping technology has advanced rapidly, which enabled the tremendous success of genome-wide association studies (GWAS) in the search of disease susceptibility loci (DSLs). However, only a small fraction of the overall predicted heritability can be explained by the DSLs discovered. One possible explanation for this ”missing heritability” phenomenon is that many causal variants are rare. The recent development of high-throughput next-generation sequencing (NGS) technology provides the instrument to look closely at these rare variants with precision and efficiency

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2

Haroun, Paul. "Genetic algorithm and data visualization." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape16/PQDD_0017/MQ37125.pdf.

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3

Lankhorst, Marc Martijn. "Genetic algorithms in data analysis." [S.l. : [Groningen] : s.n.] ; [University Library Groningen] [Host], 1996. http://irs.ub.rug.nl/ppn/142964662.

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4

Hiden, Hugo George. "Data-based modelling using genetic programming." Thesis, University of Newcastle Upon Tyne, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246137.

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5

Auton, Adam. "The estimation of recombination rates from population genetic data." Thesis, University of Oxford, 2007. http://ora.ox.ac.uk/objects/uuid:dc38045b-725d-4afc-8c76-94769db3534d.

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Genetic recombination is an important process that generates new combinations of genes on which natural selection can operate. As such, an understanding of recombination in the human genome will provide insight into the evolutionary processes that have shaped our genetic history. The aim of this thesis is to use samples of population genetic data to explore the patterns of variation in the rate of recombination in the human genome. To do this I introduce a novel means of estimating recombination rates from population genetic data. The new, computationally efficient method incorporates a model

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6

Agarwala, Vineeta. "Integrating empirical data and population genetic simulations to study the genetic architecture of type 2 diabetes." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:11120.

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Most common diseases have substantial heritable components but are characterized by complex inheritance patterns implicating numerous genetic and environmental factors. A longstanding goal of human genetics research is to delineate the genetic architecture of these traits - the number, frequencies, and effect sizes of disease-causing alleles - to inform mapping studies, elucidate mechanisms of disease, and guide development of targeted clinical therapies and diagnostics. Although vast empirical genetic data has now been collected for common diseases, different and contradictory hypotheses ha

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7

Romano, Eduardo O. "Selection indices for combining marker genetic data and animal model information /." This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-09192009-040546/.

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8

Li, Xin. "Haplotype Inference from Pedigree Data and Population Data." Cleveland, Ohio : Case Western Reserve University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1259867573.

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Thesis(Ph.D.)--Case Western Reserve University, 2010<br>Title from PDF (viewed on 2009-12-30) Department of Electrical Engineering and Computer Science Includes abstract Includes bibliographical references and appendices Available online via the OhioLINK ETD Center

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9

McCaskie, Pamela Ann. "Multiple-imputation approaches to haplotypic analysis of population-based data with applications to cardiovascular disease." University of Western Australia. School of Population Health, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0160.

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[Truncated abstract] This thesis investigates novel methods for the genetic association analysis of haplotype data in samples of unrelated individuals, and applies these methods to the analysis of coronary heart disease and related phenotypes. Determining the inheritance pattern of genetic variants in studies of unrelated individuals can be problematic because family members of the studied individuals are often not available. For the analysis of individual genetic loci, no problem arises because the unit of interest is the observed genotype. When the unit of interest is the linear combination

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10

Al-Madi, Naila Shikri. "Improved Genetic Programming Techniques For Data Classification." Diss., North Dakota State University, 2014. https://hdl.handle.net/10365/27097.

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Evolutionary algorithms are one category of optimization techniques that are inspired by processes of biological evolution. Evolutionary computation is applied to many domains and one of the most important is data mining. Data mining is a relatively broad field that deals with the automatic knowledge discovery from databases and it is one of the most developed fields in the area of artificial intelligence. Classification is a data mining method that assigns items in a collection to target classes with the goal to accurately predict the target class for each item in the data. Genetic programmin

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11

Shenoy, U. Nagaraj. "Automatic Data Partitioning By Hierarchical Genetic Search." Thesis, Indian Institute of Science, 1996. https://etd.iisc.ac.in/handle/2005/172.

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The introduction of languages like High Performance Fortran (HPF) which allow the programmer to indicate how the arrays used in the program have to be distributed across the local memories of a multi-computer has not completely unburdened the parallel programmer from the intricacies of these architectures. In order to tap the full potential of these architectures, the compiler has to perform this crucial task of data partitioning automatically. This would not only unburden the programmer but would make the programs more efficient since the compiler can be made more intelligent to take care o

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12

Shenoy, U. Nagaraj. "Automatic Data Partitioning By Hierarchical Genetic Search." Thesis, Indian Institute of Science, 1996. http://hdl.handle.net/2005/172.

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CDAC<br>The introduction of languages like High Performance Fortran (HPF) which allow the programmer to indicate how the arrays used in the program have to be distributed across the local memories of a multi-computer has not completely unburdened the parallel programmer from the intricacies of these architectures. In order to tap the full potential of these architectures, the compiler has to perform this crucial task of data partitioning automatically. This would not only unburden the programmer but would make the programs more efficient since the compiler can be made more intelligent to take

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13

Cole, Rowena Marie. "Clustering with genetic algorithms." University of Western Australia. Dept. of Computer Science, 1998. http://theses.library.uwa.edu.au/adt-WU2003.0008.

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Clustering is the search for those partitions that reflect the structure of an object set. Traditional clustering algorithms search only a small sub-set of all possible clusterings (the solution space) and consequently, there is no guarantee that the solution found will be optimal. We report here on the application of Genetic Algorithms (GAs) -- stochastic search algorithms touted as effective search methods for large and complex spaces -- to the problem of clustering. GAs which have been made applicable to the problem of clustering (by adapting the representation, fitness function,

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14

Ahsan, Nasir Computer Science &amp Engineering Faculty of Engineering UNSW. "Learning causal networks from gene expression data." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/26151.

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In this thesis we present a new model for identifying dependencies within a gene regulatory cycle. The model incorporates both probabilistic and temporal aspects, but is kept deliberately simple to make it amenable for learning from the gene expression data of microarray experiments. A key simplifying feature in our model is the use of a compression function for collapsing multiple causes of gene expression into a single cause. This allows us to introduce a learning algorithm which avoids the over-fitting tendencies of models with many parameters. We have validated the learning algorithm on si

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15

Li, Xiang, and xiali@cs rmit edu au. "Utilising Restricted For-Loops in Genetic Programming." RMIT University. Computer Science and Information Technology, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080110.122751.

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Genetic programming is an approach that utilises the power of evolution to allow computers to evolve programs. While loops are natural components of most programming languages and appear in every reasonably-sized application, they are rarely used in genetic programming. The work is to investigate a number of restricted looping constructs to determine whether any significant benefits can be obtained in genetic programming. Possible benefits include: Solving problems which cannot be solved without loops, evolving smaller sized solutions which can be more easily understood by human programmers

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16

Lei, Celestino. "Using genetic algorithms and boosting for data preprocessing." Thesis, University of Macau, 2002. http://umaclib3.umac.mo/record=b1447848.

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17

Leslie, Stephen. "Inference of Population Stratification Using Population Genetic Data." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504423.

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18

Cheng, Lulu. "Statistical Methods for Genetic Pathway-Based Data Analysis." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/52039.

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The wide application of the genomic microarray technology triggers a tremendous need in the development of the high dimensional genetic data analysis. Many statistical methods for the microarray data analysis consider one gene at a time, but they may miss subtle changes at the single gene level. This limitation may be overcome by considering a set of genes simultaneously where the gene sets are derived from the prior biological knowledge and are called "pathways". We have made contributions on two specific research topics related to the high dimensional genetic pathway data. One is to propose

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19

Liu, Dongqing. "GENETIC ALGORITHMS FOR SAMPLE CLASSIFICATION OF MICROARRAY DATA." University of Akron / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=akron1125253420.

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20

Delman, Bethany. "Genetic algorithms in cryptography /." Link to online version, 2003. https://ritdml.rit.edu/dspace/handle/1850/263.

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21

Xia, Fan, and 夏凡. "Some topics on statistical analysis of genetic imprinting data and microbiome compositional data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206673.

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Genetic association study is a useful tool to identify the genetic component that is responsible for a disease. The phenomenon that a certain gene expresses in a parent-of-origin manner is referred to as genomic imprinting. When a gene is imprinted, the performance of the disease-association study will be affected. This thesis presents statistical testing methods developed specially for nuclear family data centering around the genetic association studies incorporating imprinting effects. For qualitative diseases with binary outcomes, a class of TDTI* type tests was proposed in a general two-st

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22

Uduman, Mohamed. "Identifying the largest complete data set from ALFRED /." Link to online version, 2006. https://ritdml.rit.edu/dspace/handle/1850/1876.

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23

Romano, Eduardo. "Selection indices for combining marker genetic data and animal model information." Thesis, Virginia Tech, 1993. http://hdl.handle.net/10919/44879.

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It was suggested that marker and phenotypic information be combined in order to obtain more accurate or earlier genetic evaluations. An improvement in accuracy or time of evaluation due to utilization of marker assisted selection (MAS) increases genetic progress. Fernando and Grossman (1989) suggested including marker information directly into the Animal Model, Best Linear Unbiased Prediction system, but several problems need to be solved before their approach becomes feasible. Other selection indices were suggested but either do not use all the available information or are suitable only for e

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24

Stewart, William C. L. "Alternative models for estimating genetic maps from pedigree data /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/8975.

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25

Jochumsson, Thorvaldur. "Inferring Genetic Networks from Expression Data with Mutual Information." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-736.

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<p>Recent methods to infer genetic networks are based on identifying gene interactions by similarities in expression profiles. These methods are founded on the assumption that interacting genes share higher similarities in their expression profiles than non-interacting genes. In this dissertation this assumption is validated when using mutual information as a similarity measure. Three algorithms that calculate mutual information between expression data are developed: 1) a basic approach implemented with the histogram technique; 2) an extension of the basic approach that takes into consideratio

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26

Ayaz, Eyup Serdar. "Resonctructing Signaling Pathways From Rnai Data Using Genetic Algorithms." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613813/index.pdf.

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Cell signaling is a list of chemical reactions that are used for intercellular and intracellular communication. Signaling pathways denote these chemical reactions in a systematic manner. Today, many signaling pathways are constructed by several experimental methods. However there are still many communication skills of cells that are needed to be discovered. RNAi system allows us to see the phenotypes when some genes are removed from living cells. By observing these phenotypes, we can build signaling pathways. However it is costly in terms of time and space complexity. Furthermore, there are so

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27

Liu, Kejun. "Software and Methods for Analyzing Molecular Genetic Marker Data." NCSU, 2003. http://www.lib.ncsu.edu/theses/available/etd-07182003-122001/.

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Genetic analysis of molecular markers has allowed biologists to ask a wide variety of questions. This dissertation explores some aspects of the statistical and computational issues used in the genetic marker data analysis. Chapter 1 gives an introduction to genetic marker data, as well as a brief description to each chapter. Chapter 2 presents the different genetic analyses performed on a large data set and discusses the use of microsatellites to describe the maize germplasm and to improve maize germplasm maintenance. Considerable attention is focused on how the maize germplasm is organized an

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28

Romero, Carol Eduardo. "A genetic algorithm for reservoir characterisation using production data." Thesis, Imperial College London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394511.

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29

Tong, Dong Ling. "Genetic algorithm-neural network : feature extraction for bioinformatics data." Thesis, Bournemouth University, 2010. http://eprints.bournemouth.ac.uk/15788/.

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With the advance of gene expression data in the bioinformatics field, the questions which frequently arise, for both computer and medical scientists, are which genes are significantly involved in discriminating cancer classes and which genes are significant with respect to a specific cancer pathology. Numerous computational analysis models have been developed to identify informative genes from the microarray data, however, the integrity of the reported genes is still uncertain. This is mainly due to the misconception of the objectives of microarray study. Furthermore, the application of variou

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30

Carter, Jason W. "Testing effectiveness of genetic algorithms for exploratory data analysis." Thesis, Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/9065.

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Approved for public release; distribution is unlimited<br>Heuristic methods of solving exploratory data analysis problems suffer from one major weakness - uncertainty regarding the optimality of the results. The developers of DaMI (Data Mining Initiative), a genetic algorithm designed to mine the CCEP (Comprehensive Clinical Evaluation Program) database in the search for a Persian Gulf War syndrome, proposed a method to overcome this weakness: reproducibility -- the conjecture that consistent convergence on the same solutions is both necessary and sufficient to ensure a genetic algorithm has e

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31

Lin, Xinyi (Cindy). "Statistical Methods for High-Dimensional Data in Genetic Epidemiology." Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11326.

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Recent technological advancements have enabled us to collect an unprecedented amount of genetic epidemiological data. The overarching goal of these genetic epidemiology studies is to uncover the underlying biological mechanisms so that improved strategies for disease prevention and management can be developed. To efficiently analyze and interpret high-dimensional biological data, it is imperative to develop novel statistical methods as conventional statistical methods are generally not applicable or are inefficient. In this dissertation, we introduce three novel, powerful and computationally

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32

Li, Qiao. "Data mining and statistical techniques applied to genetic epidemiology." Thesis, University of East Anglia, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.533716.

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Genetic epidemiology is the study of the joint action of genes and environmental factors in determining the phenotypes of diseases. The twin study is a classic and important epidemiological tool, which can help to separate the underlying effects of genes and environment on phenotypes. Twin data have been widely examined using traditional methods to genetic epidemiological research. However, they provide a rich sources information related to many complex phenotypes that has the potential to be further explored and exploited. This thesis focuses on two major genetic epidemiological approaches: f

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33

ALMEIDA, MANOEL ROBERTO AGUIRRE DE. "HIBRID NEURO-FUZZY-GENETIC SYSTEM FOR AUTOMATIC DATA MINING." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5303@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Esta dissertação apresenta a proposta e o desenvolvimento de um sistema de mineração de dados inteiramente automático. O objetivo principal é criar um sistema que seja capaz de realizar a extração de informações obscuras a partir de bases de dados complexas, sem exigir a presença de um especialista técnico para configurá-lo. O sistema híbrido neuro-fuzzy hierárquico com particionamento binário (NFHB) vem apresentando excelentes resultados em tarefas de classificação de padrões e previsão, além de possuir importantes caract

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34

MEDEIROS, SHELLY CRISTIANE DAVILA. "INVERSION OF PARAMETERS IN SEISMIC DATA BY GENETIC ALGORITHMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8622@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>Esta dissertação investiga o uso de Algoritmos Genéticos aplicados em dados sísmicos com o objetivo de obter parâmetros físicos e atributos sísmicos que auxiliem na caracterização das rochas de um subsolo terrestre. Os dados sísmicos têm sido extensamente empregados no setor de exploração de petróleo. As aplicações envolvendo sísmica não se restringem na busca por novas reservas de petróleo, mas também são usadas para projetar novos poços e melhorar a produção dos reservatórios de petróleo. O levantamento de dados sísmicos permite an

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35

Minichiello, Mark Joseph. "Analysis of genetic variation data using ancestral recombination graphs." Thesis, University of Cambridge, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.613255.

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36

Jaffrezic, Florence. "Statistical models for the genetic analysis of longitudinal data." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/12274.

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The first objective of this work was to compare and contrast different methodologies for genetic analysis. As the range of all possible models can be very large in practice, it is advisable to have a preliminary idea of the covariance structure of the data, and a non-parametric approach based on the variogram was proposed. It is especially adapted for exploratory analysis when a large number of observations is available per subject over time and was applied to the analysis of daily records for milk production in dairy cattle. Model comparisons in the univariate case showed that character proce

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37

Alsulaiman, Thamer. "Detecting complex genetic mutations in large human genome data." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/6908.

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All cellular forms of life contain Deoxyribonucleic acid (DNA). DNA is a molecule that carries all the information necessary to perform both, basic and complex cellular functions. DNA is replicated to form new tissue/organs, and to pass genetic information to future generations. DNA replication ideally yield an exact copy of the original DNA. While replication generally occurs without error, it may leave DNA vulnerable to accidental changes via mistakes made during the replication process. Those changes are called mutations. Mutations range in magnitude. Yet, mutations of any magnitude range i

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38

Evenstone, Lauren. "Employing Limited Next Generation Sequence Data for the Development of Genetic Loci of Phylogenetic and Population Genetic Utility." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/2191.

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Massively parallel high throughput sequencers are transforming the scientific research by reducing the cost and time necessary to sequence entire genomes. The goal of this project is to produce preliminary genome assemblies of calliphorid flies using Life Technologies’ Ion Torrent sequencing and Illumina’s MiSeq sequencing. I located, assembled, and annotated a novel mitochondrial genome for one such fly, the little studied Chrysomya pacifica that is central to one hypothesis about blow fly evolution. With sequencing data from Chrysomya megacephala, its forensically relevant sister species, mu

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39

Chen, Li. "Searching for significant feature interaction from biological data." Diss., Online access via UMI:, 2007.

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40

Cai, Chunhui. "Identification and characterization of yeast synergistic regulatory interaction from high throughput data." HKBU Institutional Repository, 2010. http://repository.hkbu.edu.hk/etd_ra/1190.

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41

Rodríguez, Botigué Laura 1984. "Demographic insights of human north African populations using genetic data." Doctoral thesis, Universitat Pompeu Fabra, 2012. http://hdl.handle.net/10803/108336.

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The history of North Africa is extremely complex, and it has been difficult to assess from genetic and archeological data whether early populations were replaced by later migrations or if there has been continuous settlement of the region. To resolve the history of human origin and migrations in North Africa, I have used two main forms of genetic data, the maternally inherited mtDNA and 730,000 genome-wide SNPs from a genotype array in a sample set representative of the region. I have discovered that North Africa is a mosaic of an autochthonous component dating back to the Paleolithic an

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42

Lindlöf, Angelica. "Deriving Genetic Networks from Gene Expression Data and Prior Knowledge." Thesis, University of Skövde, Department of Computer Science, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-589.

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<p>In this work three different approaches for deriving genetic association networks were tested. The three approaches were Pearson correlation, an algorithm based on the Boolean network approach and prior knowledge. Pearson correlation and the algorithm based on the Boolean network approach derived associations from gene expression data. In the third approach, prior knowledge from a known genetic network of a related organism was used to derive associations for the target organism, by using homolog matching and mapping the known genetic network to the related organism. The results indicate th

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43

Gay, Jo. "Estimating the rate of gene conversion from population genetic data." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.509942.

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Hobbs, Mike. "Genetic algorithms for spatial data analysis in geographical information systems." Thesis, University of Kent, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262636.

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Sthamer, Harmen-Hinrich. "The automatic generation of software test data using genetic algorithms." Thesis, University of South Wales, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320726.

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46

Xu, Yun. "Chemometrics pattern recognition with applications to genetic and metabolomics data." Thesis, University of Bristol, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.435733.

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Kumuthini, Judit. "Extraction of genetic network from microarray data using Bayesian framework." Thesis, Cranfield University, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442547.

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48

Eisner, Eric David. "Incorporating diverse data to improve genetic network alignment with IsoRank." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/77068.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 26).<br>To more accurately predict which genes from different species have the same function (orthologs), I extend the network-alignment algorithm IsoRank to simultaneously align multiple unrelated networks over the same set of nodes. In addition to the original protein-interaction networks, I align genetic-interaction networks, gene-expression correlations, and chromosome localization data to im

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Gerbault, P. "Modeling demographic and evolutionary history : integrating genetic and archaeological data." Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/1389022/.

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In recent years, population genetic data has been used increasingly to make inferences on population history – particularly concerning the human past. However, any observed genetic data is only one outcome amongst a very large number of possibilities that can arise under the same population history; and reversely, multiple different histories can give rise to the same data. For this reason direct interpretation of patterns in genetic data to recover evolutionary history is highly problematic, and inferring evolutionary histories – including demographic and natural selection-related parameters

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Trochet, Holly. "Simple Bayesian approaches to modelling pleiotropy in genetic association data." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:a1e3d606-ef39-4ef7-981e-088d6703c04f.

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Genome-wide association studies (GWAS) have become one of the most common types of genetic studies, due to their success at finding markers associated with diseases and other traits of interest. With thousands of these studies performed in the last decade, a variety of methods have been developed to meta-analyze their results to search for variants that affect multiple traits. This thesis introduces one such method, based on approximate Bayes factors (ABFs), which relies only on effect size estimates and standard errors from GWAS. Through application to simulated data as well as three differen

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