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Tesis sobre el tema "Gene selection"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de julio de 2025

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1

Petronella, Nicholas. "Gene Conversions and Selection in the Gene Families of Primates." Thesis, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/20538.

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We used the GENECONV program, the Hsu et al. (2010) method and phylogenetic analyses to analyze the gene conversions which occurred in the growth hormone, folate receptor and trypsin gene families of six primate species. Significant positive correlations were found between sequence similarity and conversion length in all but the trypsin gene family. Converted regions, when compared to non-converted ones, also displayed a significantly higher GC-content in the growth hormone and folate receptor gene families. Finally, all detected gene conversions were found to be less frequent in conserved gen

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2

Zid, Mouldi. "Gene Conversions in the Siglec and CEA Immunoglobulin Gene Families of Primates." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/23625.

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Siglecs and CEA are two families of cell surface proteins belonging to the immunoglobulin superfamily. They are thought to be involved in cell-cell interactions and have various other biological functions. We used the GENECONV program that applies statistical tests to detect gene conversion events in each family of five primate species. For the Siglec family, we found that gene conversions are frequent between CD33rSiglec genes, but are absent between their conserved Siglec genes. For the CEA family, half of gene conversion events detected are located in coding regions. A significant positive

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3

Liu, Zhilin. "Gene expression profiling of bovine ovarian follicular selection." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4490.

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Thesis (Ph.D.)--University of Missouri-Columbia, 2006.<br>The entire dissertation/thesis text is included in the research.pf file; the official abstract appears in the short.pf file (which also appears in the research.pf); a non-technical general description, or public abstract, appears in the public.pf file. Title from title screen of research.pf file (viewed on May 6, 2009) Vita. Includes bibliographical references.

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4

Huisman, Jisca. "Gene Flow and Natural Selection in Atlantic Salmon." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for biologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-16991.

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5

Chen, Li. "Ranking-Based Methods for Gene Selection in Microarray Data." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/3888.

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DNA microarrays have been used for the purpose of monitoring expression levels of thousands of genes simultaneously and identifying those genes that are differentially expressed. One of the major goals of microarray data analysis is the detection of differentially expressed genes across two kinds of tissue samples or samples obtained under two experimental conditions. A large number of gene detection methods have been developed and most of them are based on statistical analysis. However the statistical analysis methods have the limitations due to the small sample size and unknown distribution

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6

Perucchini, Matteo. "The cervid PrP gene : patterns of variability and selection." Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/15634.

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Variation at codon 132 of the <i>Cervus canadensis </i>(wapiti) <i>PRNP</i> has been claimed to modulate Chronic Wasting Disease (CWD), a relatively new TSE affecting cervid species and currently the only TSE naturally affecting both captive and free-ranging populations. Codon 132 corresponds to the human codon 129 and variation at this position has been associated with TSE-related balancing selection in humans. This thesis investigated the genetic variability and selective patterns of coding and non-coding regions of <i>PRNP</i> in free-ranging populations of <i>C. Canadensis </i>and <i>C. el

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7

Medeiros, Lucas Paoliello de. "Coevolution in mutualistic networks: gene flow and selection mosaics." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/41/41134/tde-17102017-154829/.

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Ecological interactions such as predation, competition, and mutualism are important forces that influence species evolution. Coevolution is defined as reciprocal evolutionary change in interacting species. The Geographic Mosaic Theory of Coevolution (GMTC) provides a theoretical framework to explain how collections of populations should coevolve across space. Two fundamental aspects of the GMTC are gene flow among populations and the presence of selection mosaics, which are collections of localities with particular selection regimes. Several studies have explored how phenotypic trait matching

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8

Dai, Xiaotian. "Novel Statistical Models for Quantitative Shape-Gene Association Selection." DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/6856.

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Other research reported that genetic mechanism plays a major role in the development process of biological shapes. The primary goal of this dissertation is to develop novel statistical models to investigate the quantitative relationships between biological shapes and genetic variants. However, these problems can be extremely challenging to traditional statistical models for a number of reasons: 1) the biological phenotypes cannot be effectively represented by single-valued traits, while traditional regression only handles one dependent variable; 2) in real-life genetic data, the number of cand

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9

Riddoch, B. "Selection component analysis of the PGI polymorphism in Sphaeroma rugicauda." Thesis, University of Essex, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.378440.

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10

Panji, Sumir. "Identification of bacterial pathogenic gene classes subject to diversifying selection." Thesis, University of the Western Cape, 2009. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_5842_1297942831.

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<p>Availability of genome sequences for numerous bacterial species comprising of different bacterial strains allows elucidation of species and strain specific adaptations that facilitate their survival in widely fluctuating micro-environments and enhance their pathogenic potential. Different bacterial species use different strategies in their pathogenesis and the pathogenic potential of a bacterial species is dependent on its genomic complement of virulence factors. A bacterial virulence factor, within the context of this study, is defined as any endogenous protein product encoded by a gene th

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11

Wood, S. Morwenna. "Oxygen sensing and gene expression : selection and analysis of mutant cells." Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297427.

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12

Nasiadka, Andrzej. "Gene-regulatory interactions and mechanisms of target gene selection of the Drosophila homeodomain protein Fushi tarazu." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ63722.pdf.

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13

Liu, Yushi. "Properties of the SCOOP Method of Selecting Gene Sets." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1280163360.

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14

Berggren, Bremdal Karin. "Evolution of MHC Genes and MHC Gene Expression." Doctoral thesis, Uppsala universitet, Evolutionsbiologi, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-122011.

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Polymorphism in coding regions and regions controlling gene expression is the major determinant of adaptive differences in natural populations. Genes of the major histocompatibility complex (MHC) possess a high level of genetic variation, which is maintained by selection over long coalescence times. MHC genes encode antigen-presenting molecules in the adaptive immune system, which protects the host from infectious diseases. However, MHC molecules may also present self-peptides and for most autoimmune diseases there is a genetic factor associated with the MHC. MHC genes have been used to learn

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15

Dong, Chunrong. "A housekeeping gene based procedure for the selection of differentially expressed genes for Affymetrix microarray experiments." Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1278088559.

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16

Assareh, Amin. "OPTIMIZING DECISION TREE ENSEMBLES FOR GENE-GENE INTERACTION DETECTION." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1353971575.

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17

Freudenberg, Johannes M. "Bayesian Infinite Mixture Models for Gene Clustering and Simultaneous Context Selection Using High-Throughput Gene Expression Data." University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1258660232.

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18

Muttalib, Shahin. "The balance between selection and gene flow evaluated in threespine stickleback." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110425.

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Many populations seem adapted to their environment, through a match between their phenotype and habitat or resources. However, significant maladaptation is widespread, perhaps partly due to gene flow between populations, which prevents tracking a local optimum, by introducing alleles adapted to alternative conditions. Threespine stickleback show significant adaptive divergence over a variety of phenotypic traits, and the divergent lake-stream pairs of Vancouver Island illustrate the balance between selection and gene flow that exists in natural populations. In my thesis, I use the threespine s

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19

Song, Youqiang. "Development of polymorphic molecular markers for bovine gene mapping and selection." Thesis, University of Reading, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262235.

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20

Osborne, Owen Gregory. "Genomic analyses of gene flow and selection during diversification in Senecio." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:ffe5fb97-f0d0-4f6f-aed0-8cbb3226c1e5.

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Diversifying selection and gene flow were traditionally viewed as antagonistic forces, with diversifying selection promoting adaptation and speciation, and gene flow opposing them. However, their roles are far more complex than this. While gene flow can prevent speciation or initiate despeciation, it can also generate new hybrid species. Similarly, while adaptive divergence can be wiped out by gene flow, new adaptive variation can be introduced via hybridisation. The relative frequency of these outcomes, and indeed the frequency of gene flow and diversifying selection in general are largely un

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21

Canul, Reich Juana. "An Iterative Feature Perturbation Method for Gene Selection from Microarray Data." Scholar Commons, 2010. https://scholarcommons.usf.edu/etd/1588.

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Gene expression microarray datasets often consist of a limited number of samples relative to a large number of expression measurements, usually on the order of thousands of genes. These characteristics pose a challenge to any classification model as they might negatively impact its prediction accuracy. Therefore, dimensionality reduction is a core process prior to any classification task. This dissertation introduces the iterative feature perturbation method (IFP), an embedded gene selector that iteratively discards non-relevant features. IFP considers relevant features as those which after pe

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22

Lewis, Samuel Howard. "Evolution of Dipteran Argonaute genes through duplication, selection and functional specialisation." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/19569.

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The RNA interference (RNAi) mechanism is a conserved system of nucleic acid manipulation, based on the interaction between small RNA guide molecules and Argonaute effector proteins. RNAi pathways are found in the vast majority of eukaryotes, and have diversified into a broad array of functions including gene regulation, antiviral immunity and transposable element (TE) suppression. Many of these functional innovations coincide with duplication of Argonaute genes, suggesting that gene duplication may be a key driving force in the diversification of RNAi. However, few studies have explicitly inve

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23

Xu, Yaomin. "New Clustering and Feature Selection Procedures with Applications to Gene Microarray Data." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1196144281.

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24

Errington, Stephen J. "Target selection for antisense oligonucleotide induced exon skipping in the dystrophin gene." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2004. https://ro.ecu.edu.au/theses/794.

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Duchene Muscular Dystrophy (DMD), and the milder allelic Becker muscular dystrophy (EMD), are X-linked recessive muscle wasting disorders characterised by mutations in the dystrophin gene. DMD occurs at a frequency of approximately 1 in 3500 male newborns and life expectancy is typically less than 30 years. Due to progressive muscle wasting, affected boys are restricted to a wheelchair by the age of 12 years. The most common cause of death is pneumonia, compounded by cardiac involvement. Mutations that disrupt the dystrophin reading frame, or prevent the synthesis of either terminus, preclude

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25

Makrinou, Eleni. "A cDNA selection approach to isolate Y-linked genes expressed in testis." Thesis, University College London (University of London), 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326172.

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26

Venegas-Ortiz, Juan. "Statistical mechanics of gene competition." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/9372.

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Statistical mechanics has been applied to a wide range of systems in physics, biology, medicine and even anthropology. This theory has been recently used to model the complex biochemical processes of gene expression and regulation. In particular, genetic networks offer a large number of interesting phenomena, such as multistability and oscillatory behaviour, that can be modelled with statistical mechanics tools. In the first part of this thesis we introduce gene regulation, genetic switches, and the colonization of a spatially structured media. We also introduce statistical mechanics and some

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27

Akhimienmhonan, Douglas. "An economic analysis of gene marker assisted seedstock selection in beef cattle." Thesis, University of British Columbia, 2006. http://hdl.handle.net/2429/96.

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This study analyzes the economic impact of a recent gene marker innovation for seedstock selection in beef cattle. Gene markers are being developed for many beef cattle attributes; this study focused on the tenderness quality of beef using two categories: tender and tough. The study begins by describing conventional procedures for seedstock selection, the science which underlies selection by gene markers and other non-genetic procedures currently being used to improve beef tenderness. After describing the commercialization of the gene marker innovation, a stylized model of a beef supply chain

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28

Coop, Graham M. "The likelihood of gene trees under selective models." Thesis, University of Oxford, 2004. http://ora.ox.ac.uk/objects/uuid:ba97d36c-61c1-40c8-a1f4-e7ddc8918d5b.

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The extent to which natural selection shapes diversity within populations is a key question for population genetics. Thus, there is considerable interest in quantifying the strength of selection. In this thesis a full likelihood approach for inference about selection at a single site within an otherwise neutral fully-linked sequence of sites is developed. Integral to many of the ideas introduced in this thesis is the reversibility of the diffusion process, and some past approaches to this concept are reviewed. A coalescent model of evolution is used to model the ancestry of a sample of DNA seq

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29

Steiger, Edgar [Verfasser]. "Efficient Sparse-Group Bayesian Feature Selection for Gene Network Reconstruction / Edgar Steiger." Berlin : Freie Universität Berlin, 2018. http://d-nb.info/1170876633/34.

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30

Fernando, Himesh. "Selection of G-quadruplex specific proteins and their effects on gene expression." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.598998.

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G-quadruplexes in the promoters of oncogenes have been identified as potential therapeutic targets for the regulation of gene transcription by quadruplex-binding molecules. KIT is a tyrosine kinase receptor found on the cell membrane, and forms part of the cell signalling pathway. Certain mutations within it result in constitutive activation leading to uncontrolled cell proliferation. Elevated levels of KIT have been reported in most gastrointestinal cancer cases, hence making it a prime anti cancer target. <i>c-kit,</i> the gene encoding KIT, contains a G-rich sequence in its promoter. With

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31

McDonald, Kenneth W. "Gene Expression and Phenotype Response of Drosophila melanogaster to Selection." Digital Commons @ East Tennessee State University, 2008. https://dc.etsu.edu/etd/1967.

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The evolution of phenotypic plasticity is currently a topic of paramount interest in a diverse field of sub-disciplines. Salience is placed by all fields in describing the interaction of selection and phenotypic plasticity and the consequence of this interaction more broadly on evolution. Lacking in the discussion is substantial empirical description of genotype/phenotype interactions that by definition constitute the plastic response to novel and stressful environments. Here, I present empirical observations that bring the interaction of genotype and phenotype into focus. Drosophila melanogas

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32

McCluskey, Braedan. "Genome Evolution and Gene Expression Divergence in the Genus Danio." Thesis, University of Oregon, 2016. http://hdl.handle.net/1794/20484.

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Genus Danio includes zebrafish (Danio rerio) and several other phenotypically diverse species. To understand the history of these species and how they acquired the genetic differences underlying their diverse phenotypes, I performed two phylogenomic studies using Restriction-Site Associated DNA Sequencing and DNA hybridization-based exome enrichment. The results of these studies highlight important methodological considerations applicable to future experiments across taxa. Furthermore, these studies provide detailed understanding of the relationships within Danio including extensive introgress

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33

Chen, Xiaohui. "Comparisons of statistical modeling for constructing gene regulatory networks." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/4068.

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Genetic regulatory networks are of great importance in terms of scientific interests and practical medical importance. Since a number of high-throughput measurement devices are available, such as microarrays and sequencing techniques, regulatory networks have been intensively studied over the last decade. Based on these high-throughput data sets, statistical interpretations of these billions of bits are crucial for biologist to extract meaningful results. In this thesis, we compare a variety of existing regression models and apply them to construct regulatory networks which span trancription f

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34

Yu, Guoqiang. "Machine Learning to Interrogate High-throughput Genomic Data: Theory and Applications." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/28980.

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The missing heritability in genome-wide association studies (GWAS) is an intriguing open scientific problem which has attracted great recent interest. The interaction effects among risk factors, both genetic and environmental, are hypothesized to be one of the main missing heritability sources. Moreover, detection of multilocus interaction effect may also have great implications for revealing disease/biological mechanisms, for accurate risk prediction, personalized clinical management, and targeted drug design. However, current analysis of GWAS largely ignores interaction effects, partly due t

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35

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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36

Shu, Cindy Chia-Fan Biotechnology &amp Biomolecular Sciences Faculty of Science UNSW. "Selection and isolation of high producing mammalian clones." Awarded by:University of New South Wales, 2007. http://handle.unsw.edu.au/1959.4/37031.

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This research studied recombinant DNA-derived protein expression utilising expression vectors containing IRES sequences to link the gene of interest with the gene encoding selectable marker in mammalian cell cultures. Polycistronic expression constructs utilising internal ribosome entry site (IRES) can link unrelated genes under control of a single promoter. Transient study on the IRESlinked gene expression was performed. It was possible to standardise the level of protein expression to plasmid number by determining the number of free plasmids in the cytoplasm. The expression of a selectable m

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37

Nordling, Torbjörn E. M. "Robust inference of gene regulatory networks : System properties, variable selection, subnetworks, and design of experiments." Doctoral thesis, KTH, Reglerteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-120830.

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In this thesis, inference of biological networks from in vivo data generated by perturbation experiments is considered, i.e. deduction of causal interactions that exist among the observed variables. Knowledge of such regulatory influences is essential in biology. A system property–interampatteness–is introduced that explains why the variation in existing gene expression data is concentrated to a few “characteristic modes” or “eigengenes”, and why previously inferred models have a large number of false positive and false negative links. An interampatte system is characterized by strong INTERact

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38

Bueno, Maria Rita Spina. "Níveis de seleção: uma avaliação a partir da teoria do \"gene egoísta\"." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/8/8133/tde-03092009-145224/.

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Esta dissertação de mestrado aborda a controvérsia em torno de qual é o nível biológico no qual a seleção natural atua, com ênfase na proposta de Richard Dawkins do gene egoísta e nas questões que surgem em torno da mesma. Examina-se um panorama de questões de filosofia da biologia abordadas a partir do problema dos níveis nos quais a seleção natural atua. Esperamos que ao avaliar o impacto da teoria do gene egoísta na problemática evolutiva, consigamos compreender sua importância. O objetivo deste trabalho é filosófico, delineando as questões e clarificando alguns termos do debate, sem se pro

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39

Zhang, Yiran. "Bayesian Variable Selection for High-Dimensional Data with an Ordinal Response." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1565283865507018.

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40

Tjärnberg, Andreas. "Exploring the Boundaries of Gene Regulatory Network Inference." Doctoral thesis, Stockholms universitet, Institutionen för biokemi och biofysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-122149.

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To understand how the components of a complex system like the biological cell interact and regulate each other, we need to collect data for how the components respond to system perturbations. Such data can then be used to solve the inverse problem of inferring a network that describes how the pieces influence each other. The work in this thesis deals with modelling the cell regulatory system, often represented as a network, with tools and concepts derived from systems biology. The first investigation focuses on network sparsity and algorithmic biases introduced by penalised network inference p

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41

Broc, Camilo. "Variable selection for data aggregated from different sources with group of variable structure." Thesis, Pau, 2019. http://www.theses.fr/2019PAUU3048.

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Durant les dernières décennies, la quantité de données disponibles en génétique a consi-dérablement augmenté. D’une part, une amélioration des technologies de séquençage demolécules a permis de réduire fortement le coût d’extraction du génome humain. D’autrepart, des consortiums internationaux d’institutions ont permis la mise en commun de lacollecte de données sur de larges populations. Cette quantité de données nous permetd’espérer mieux comprendre les mécanismes régissant le fonctionnement de nos cellules.Dans ce contexte, l’épidémiologie génétique est un domaine cherchant à déterminer lare

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42

Ha, Sook Shin. "Dimensionality Reduction, Feature Selection and Visualization of Biological Data." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/77169.

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Due to the high dimensionality of most biological data, it is a difficult task to directly analyze, model and visualize the data to gain biological insight. Thus, dimensionality reduction becomes an imperative pre-processing step in analyzing and visualizing high-dimensional biological data. Two major approaches to dimensionality reduction in genomic analysis and biomarker identification studies are: Feature extraction, creating new features by combining existing ones based on a mapping technique; and feature selection, choosing an optimal subset of all features based on an objective function.

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43

Kontos, Kevin. "Gaussian graphical model selection for gene regulatory network reverse engineering and function prediction." Doctoral thesis, Universite Libre de Bruxelles, 2009. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210301.

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One of the most important and challenging ``knowledge extraction' tasks in bioinformatics is the reverse engineering of gene regulatory networks (GRNs) from DNA microarray gene expression data. Indeed, as a result of the development of high-throughput data-collection techniques, biology is experiencing a data flood phenomenon that pushes biologists toward a new view of biology--systems biology--that aims at system-level understanding of biological systems.<p><p>Unfortunately, even for small model organisms such as the yeast Saccharomyces cerevisiae, the number p of genes is much larger than th

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44

Peng, Ho-Lan, and 彭郃嵐. "Gene Selection Methods." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/03200922452706313969.

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碩士<br>國立交通大學<br>統計學研究所<br>96<br>It's a trend to use statistical methods in medical science. If the genes which cause the diseases could be found, it might be helpful to nowadays medical field. In this article, we proposed several methods to find the probable influential genes which are over- or down-expressed in some but not all samples in a disease group. Those methods include WORT (weight outlier robust t-statistic), WOS (weight outlier sum), PGM (the MLE of probability of Gaussian mixture model), TGM (T-statistic of Gaussian mixture model), QGM(Quantile of Gaussian mixture model), and Bayes

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45

Chang, Shu-Jing, and 張淑淨. "Nonlinear Gene Selection Method." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/8ugnmr.

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碩士<br>國立交通大學<br>統計學研究所<br>92<br>Microarray data contains large number of p genes (usually several thousands) and small number of n patients (usually nearly 100 or less). The problem of identifying the features best discriminate among the classes to improve the ability of a classifier is known as feature selection. Some current feature selection methods and the problem of dealing with "large p, small n" are reviewed. The Support Vector Machines (SVMs) has proofed excellent performance in practice as a classification methodology. For linear classification problem, this paper studies the followin

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46

Tseng, Yen-Cheng, and 曾彥誠. "Improving Target Gene Selection in Microarray Data of Ovarian CancerImproving Target Gene Selection in Microarray Data of Ovarian CancerImproving Target Gene Selection in Microarray Data of Ovarian CancerImproving Target Gene Selection in Microarray." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/02746016456521864581.

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碩士<br>華梵大學<br>資訊管理學系碩士班<br>97<br>The Cancers may be one of the nightmares of the humanity in advances into 22 century. Furthermore, the increase speed of cancer has surpassed the scope which the humanity can understand. Taking this into consideration, scientists have transformed passive role into the steer seeker in the domain of biomedicine. Because of precious pathology material and the mutually union project of Human Genome, it is possible to find the production reason of cancer cell and the rule in the humanity's huge gene labyrinth. Without definite reasons, the ovarian cancer is one of c

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Lu, Yu-Lun, and 陸宇綸. "Gene Expression Normalization by GO based Housekeeping Gene Selection." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/xgd29k.

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碩士<br>國立臺灣海洋大學<br>資訊工程學系<br>102<br>High throughput RNA-seq analysis provides a powerful tool for revealing relationships between gene expression level and biological function of proteins. To discover differentially expressed genes among various RNA-seq datasets obtained from different experimental designs, an appropriate normalization method for calibrating multiple experimental datasets is the first challenging problem. In this thesis, a novel normalization method to facilitate biologists in selecting a set of suitable housekeeping genes for inter-sample normalization is proposed. The approac

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Chen, Yu-Chao, and 陳昱超. "Key Gene Selection in Microarray Using Sequential Forward Selection Strategy." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/7c578t.

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碩士<br>國立臺中科技大學<br>流通管理系碩士班<br>101<br>High dimension of feature space、low instance amount、and only a limited number of key genes critical for bioinformation classification problems are three characteristics in the analysis of microarray. On one hand, the selection of discriminative genes is important. On the other hand, a collection of discriminative genes do not necessarily lead to good classification quality. This is because some attributes could likely possess the similar classification effects and in turn lead to the redundant classification results. In order to generate the subsets of gene

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Swartz, Michael D. "Stochastic search gene suggestion: Hierarchical Bayesian model selection meets gene mapping." Thesis, 2004. http://hdl.handle.net/1911/18711.

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This dissertation introduces a novel approach for addressing the complexities of mapping a complex disease by adjusting a Bayesian Model Selection method. Mapping the genes for a complex disease, such as Rheumatoid Arthritis, involves finding multiple genetic loci that may contribute to the onset of the disease. Pairwise testing of the loci leads to the problem of multiple testing. To avoid multiple tests, one can look at haplotypes, or linear sets of loci, but this results in a contingency table with sparse counts, especially when using marker loci with multiple alleles. In order to jointly c

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Ke, Chao-Hsuan, and 柯兆軒. "Two-Stage Gene Selection Algorithms for Classification of Gene Expression Data." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/85395768415812242759.

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碩士<br>國立高雄應用科技大學<br>電子與資訊工程研究所碩士班<br>96<br>The microarray is a medical diagnostic tool with good efficiency, and it was used for analyzing the behavior characteristic between the gene and disease by the extensive one at present. Microarray data are characterized by a high dimension, which could be analyzed more than thousand of genes and diseases simultaneously. However, it will lead to need more computation time when it is implemented on classification. Many previous literatures showed the feature (gene) selection has some advantage, such as gene extraction which influences classification acc

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