Relevant bibliographies by topics / Gene selection

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Gene selection'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Gene selection"

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Liu, Junjie, Peng Li, Liuyang Lu, Lanfen Xie, Xiling Chen, and Baizhong Zhang. "Selection and evaluation of potential reference genes for gene expression analysis in Avena fatua Linn." Plant Protection Science 55, No. 1 (2018): 61–71. http://dx.doi.org/10.17221/20/2018-pps.

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Eight commonly used candidate reference genes, 18S ribosomal RNA (rRNA) (18S), 28S rRNA (28S), actin (ACT), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1 alpha (EF1α), ribosomal protein L7 (RPL7), Alpha-tubulin (α-TUB), and TATA box binding protein-associated factor (TBP), were evaluated under various experimental conditions to assess their suitability in different developmental stages, tissues and herbicide treatments in Avena fatua. The results indicated the most suitable reference genes for the different experimental conditions. For developmental stages, 28S and EF1α
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R, Dr Prema. "Feature Selection for Gene Expression Data Analysis – A Review." International Journal of Psychosocial Rehabilitation 24, no. 5 (2020): 6955–64. http://dx.doi.org/10.37200/ijpr/v24i5/pr2020695.

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Lee, K. E., N. Sha, E. R. Dougherty, M. Vannucci, and B. K. Mallick. "Gene selection: a Bayesian variable selection approach." Bioinformatics 19, no. 1 (2003): 90–97. http://dx.doi.org/10.1093/bioinformatics/19.1.90.

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Klee, Eric W., Stephen C. Ekker, and Lynda B. M. Ellis. "Target selection forDanio rerio functional genomics." genesis 30, no. 3 (2001): 123–25. http://dx.doi.org/10.1002/gene.1045.

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Hicham, Omara, Lazaar Mohamed, and Tabii Youness. "Effect of Feature Selection on Gene Expression Datasets Classification Accuracy." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3194–203. https://doi.org/10.11591/ijece.v8i5.pp3194-3203.

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Feature selection attracts researchers who deal with machine learning and data mining. It consists of selecting the variables that have the greatest impact on the dataset classification, and discarding the rest. This dimentionality reduction allows classifiers to be fast and more accurate. This paper traits the effect of feature selection on the accuracy of widely used classifiers in literature. These classifiers are compared with three real datasets which are pre-processed with feature selection methods. More than 9% amelioration in classification accuracy is observed, and k-means appears to
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Tsakas, SC. "Species versus gene selection." Genetics Selection Evolution 21, no. 3 (1989): 247. http://dx.doi.org/10.1186/1297-9686-21-3-247.

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Greenspan, R. J. "Selection, Gene Interaction, and Flexible Gene Networks." Cold Spring Harbor Symposia on Quantitative Biology 74 (January 1, 2009): 131–38. http://dx.doi.org/10.1101/sqb.2009.74.029.

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Nesvadbová, M., and A. Knoll. "Evaluation of reference genes for gene expression studies in pig muscle tissue by real-time PCR." Czech Journal of Animal Science 56, No. 5 (2011): 213–16. http://dx.doi.org/10.17221/1428-cjas.

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The selection of reference genes is essential for gene expression studies when using a real-time quantitative polymerase chain reaction (PCR). Reference gene selection should be performed for each experiment because the gene expression level may be changed in different experimental conditions. In this study, the stability of mRNA expression was determined for seven genes: HPRT1, RPS18, NACA, TBP, TAF4B, RPL32 and OAZ1. The stability of these reference genes was investigated in the skeletal muscle tissue of pig foetuses, piglets and adult pigs using real-time quantitative PCR and SYBR green che
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V, Sudha, and Girijamma H. A. "SCDT: FC-NNC-structured Complex Decision Technique for Gene Analysis Using Fuzzy Cluster based Nearest Neighbor Classifier." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 6 (2018): 4505–18. https://doi.org/10.11591/ijece.v8i6.pp4505-4518.

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In many diseases classification an accurate gene analysis is needed, for which selection of most informative genes is very important and it require a technique of decision in complex context of ambiguity. The traditional methods include for selecting most significant gene includes some of the statistical analysis namely 2-Sample-T-test (2STT), Entropy, Signal to Noise Ratio (SNR). This paper evaluates gene selection and classification on the basis of accurate gene selection using structured complex decision technique (SCDT) and classifies it using fuzzy cluster based nearest neighborclassifier
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Kaviani, Mina, Paul H. Goodwin, and David M. Hunter. "Differences in Gene Expression of Pear Selections Showing Leaf Curling or Leaf Reddening Symptoms Due to Pear Decline Phytoplasma." Plants 11, no. 3 (2022): 427. http://dx.doi.org/10.3390/plants11030427.

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While host gene expression has been related to symptoms associated with different phytoplasma diseases, it is unknown why some phytoplasmas are associated with different symptoms in genotypes of the same plant species. Pear tree selections showed symptoms of either leaf reddening (selection 8824-1) or leaf curling (selection 9328-1) associated with pear decline (PD) phytoplasma presence. PD populations were similar in leaves and shoots of the two selections, but in the roots, populations were significantly lower in selection 8824-1 than in 9328-1, indicating greater resistance. For host carboh
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Dissertations / Theses on the topic "Gene selection"

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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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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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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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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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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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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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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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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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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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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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Books on the topic "Gene selection"

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Jones, Danielle Angelina. Coalescent models of gene conversion with and without selection. Harvard University, 2009.

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Sexton, Ed. Dawkins and the selfish gene. Icon, 2001.

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Bernhard, Korn, ed. Positional cloning by Exon trapping and cDNA selection. Wiley, 1999.

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Collins, Warwick. A silent gene theory of evolution. University of Buckingham Press, 2009.

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Dawkins, Richard. The selfish gene. 3rd ed. Oxford University Press, 2006.

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Dawkins, Richard. The Selfish Gene. Oxford University Press, 1989.

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Dawkins, Richard. The Selfish Gene. Oxford University Press, 1999.

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Dawkins, Richard. The extended phenotype: The long reach of the gene. Oxford University Press, 1989.

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Hamilton, Arnold Frances, and Georgiou George, eds. Directed enzyme evolution: Screening and selection methods. Humana Press, 2003.

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Foster, Charles A. The selfless gene: Living with God and Darwin. Thomas Nelson, 2009.

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Book chapters on the topic "Gene selection"

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Chernomas, Robert, Ian Hudson, and Gregory Chernomas. "Unnatural Selection." In The American Gene. Routledge, 2025. https://doi.org/10.4324/9781003571629-3.

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Kriegler, Michael. "Selection and Amplification." In Gene Transfer and Expression. Palgrave Macmillan UK, 1990. http://dx.doi.org/10.1007/978-1-349-11891-5_6.

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Goodnight, Charles J. "Gene Interaction and Selection." In Plant Breeding Reviews. John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470650240.ch12.

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Rodriguez-Grande, Jorge, and Raul Fernandez-Lopez. "Measuring Plasmid Conjugation Using Antibiotic Selection." In Horizontal Gene Transfer. Springer US, 2019. http://dx.doi.org/10.1007/978-1-4939-9877-7_6.

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Bradshaw, John E. "Gene Expression and Selection of Major Genes." In Plant Breeding: Past, Present and Future. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23285-0_5.

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Rothenberg, S. Michael, Joan Fisher, David Zapol, et al. "Intracellular Combinatorial Chemistry with Peptides in Selection of Caspase-like Inhibitors." In Gene Therapy. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72160-1_18.

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Hust, Michael, Stefan Dübel, and Thomas Schirrmann. "Selection of Recombinant Antibodies From Antibody Gene Libraries." In Gene Function Analysis. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-547-3_14.

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Hust, Michael, André Frenzel, Thomas Schirrmann, and Stefan Dübel. "Selection of Recombinant Antibodies from Antibody Gene Libraries." In Gene Function Analysis. Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-721-1_14.

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de Souza, Bruno Feres, and André C. P. L. F. de Carvalho. "Gene Selection Using Genetic Algorithms." In Biological and Medical Data Analysis. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30547-7_48.

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Hudson, Richard R., and Norman L. Kaplan. "Gene Trees with Background Selection." In Non-Neutral Evolution. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2383-3_12.

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Conference papers on the topic "Gene selection"

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Aouf, Mohamad, Amr Sharawi, Khaled Samir, Sultan Almotatiri, Abdulla Bajahzar, and Ghada Kareem. "Gene Expression Data For Gene Selection Using Ensemble Based Feature Selection." In 2019 Ninth International Conference on Intelligent Computing and Information Systems (ICICIS). IEEE, 2019. http://dx.doi.org/10.1109/icicis46948.2019.9014722.

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Kumar, Rachit, David Zhang, and Marylyn DeRiggi Ritchie. "Genetic Algorithm Selection of Interacting Features (GASIF) for Selecting Biological Gene-Gene Interactions." In GECCO '24: Genetic and Evolutionary Computation Conference. ACM, 2024. http://dx.doi.org/10.1145/3638529.3654159.

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Liu, Quanzhong, Yang Zhang, Yong Wang, and Zhengguo Hu. "Study of Informative Gene Selection for Gene Expression Profiles." In 2009 WRI Global Congress on Intelligent Systems. IEEE, 2009. http://dx.doi.org/10.1109/gcis.2009.94.

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Mitra, P., and D. D. Majumder. "Feature selection and gene clustering from gene expression data." In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. IEEE, 2004. http://dx.doi.org/10.1109/icpr.2004.1334213.

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Wang, Fei, and Tao Li. "Gene Selection via Matrix Factorization." In 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering. IEEE, 2007. http://dx.doi.org/10.1109/bibe.2007.4375686.

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Yildiz, Oktay, Mesut Tez, H. Sakir Bilge, M. Ali Akcayol, and Inan Guler. "Gene selection for breast cancer." In 2012 20th Signal Processing and Communications Applications Conference (SIU). IEEE, 2012. http://dx.doi.org/10.1109/siu.2012.6204693.

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Marvi-Khorasani, Hanieh, and Hamid Usefi. "Feature Clustering Towards Gene Selection." In 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). IEEE, 2019. http://dx.doi.org/10.1109/icmla.2019.00240.

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Zotova, L., A. Zhumalin, A. Gajimuradova, I. Zhirnova, F. Abdulloyеv, and A. Nuralov. "USING OF RHT (-B1A, -B1B, D1A, D1B) SEMI-DWARFISM GENES AND COARSE-GRAINED TAGW8-B1A, TAGS 5-3A GENES FOR INCREASING THE PRODUCTIVITY OF SPRING WHEAT." In X Международная конференция молодых ученых: биоинформатиков, биотехнологов, биофизиков, вирусологов и молекулярных биологов — 2023. Novosibirsk State University, 2023. http://dx.doi.org/10.25205/978-5-4437-1526-1-323.

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To speed up the selection process of hybrids and the selection of parental forms for crosses, it is important to pay attention to both the phenotypic and genetic potential of plants. In order to increase yields by selecting optimal parameters for wheat selection based on short-stemmed and coarse-grained characteristics in a dry climate, we studied the genes of the “green revolution” group Rht and coarse-grained TaGW, TaGS, and carried out a correlation analysis between the genetic potential of wheat varieties and hybrids and their phenotypic manifestation in drought conditions. The results of
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Sounbuli, Kh, L. A. Alekseeva, O. V. Markov, A. V. Sen’kova, I. A. Savin, and N. L. Mironova. "SELECTION OF REFERENCE GENES FOR QUANTITATIVE RT-PCR OF SPLENIC NEUTROPHILS FROM HEALTHY AND TUMOR-BEARING MICE." In XI МЕЖДУНАРОДНАЯ КОНФЕРЕНЦИЯ МОЛОДЫХ УЧЕНЫХ: БИОИНФОРМАТИКОВ, БИОТЕХНОЛОГОВ, БИОФИЗИКОВ, ВИРУСОЛОГОВ, МОЛЕКУЛЯРНЫХ БИОЛОГОВ И СПЕЦИАЛИСТОВ ФУНДАМЕНТАЛЬНОЙ МЕДИЦИНЫ. IPC NSU, 2024. https://doi.org/10.25205/978-5-4437-1691-6-277.

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The expression of reference genes in neutrophils can change dramatically according to the immune status of the organism, which leads to incorrect conclusions when analyzing the results of quantitative RT-PCR. In this study, we investigated gene expression stability of 10 reference genes in the splenic neutrophils of healthy and tumor-bearing mice. Hprt1 was proposed as the most applicable stable-expressed reference gene.
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Wang, Shulin, Huowang Chen, and Shutao Li. "Gene Selection Using Neighborhood Rough Set from Gene Expression Profiles." In 2007 International Conference on Computational Intelligence and Security (CIS 2007). IEEE, 2007. http://dx.doi.org/10.1109/cis.2007.169.

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Reports on the topic "Gene selection"

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Hayward, Simon W. Therapy Selection by Gene Profiling. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada491350.

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Hayward, Simon W. Therapy Selection by Gene Profiling. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada454306.

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Hayward, Simon W. Therapy Selection by Gene Profiling. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada426169.

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Dunham, Rex A., Boaz Moav, Thomas Chen, and Benzion Cavari. Expression and Inheritance of Growth Hormone Gene Constructs and Selective Breeding of Transgenic Farmed Fish. United States Department of Agriculture, 1994. http://dx.doi.org/10.32747/1994.7568774.bard.

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Objectives: To accomplish stable expression, inheritance of transgenes and growth improvement in transgenic channel catfish, Ictalurus punctatus, and common carp, Cyprinus carpio, containing growth hormone (GH) genes, develop transgenic fish with all fish constructs, determine the relationships between copy number, expression and growth, determine the combined affect of selective breeding and gene transfer and assess environmental risk of transgenic fish. To develop mechanisms of triploidization for transgenic carp. Results: Performance of transgenic channel catfish was made uniform by selecti
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Curiel, David T., Gene Siegal, and Minghui Wang. A Double Selection Approach to Achieve Specific Expression of Toxin Genes for Ovarian Cancer Gene Therapy. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada485589.

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Curiel, David T., Gene Siegal, and Minghui Wang. A Double Selection Approach to Achieve Specific Expression of Toxin Genes for Ovarian Cancer Gene Therapy. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada472761.

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Savageau, Michael A. Selection and Computational Potential of Gene Control Elements and Their Circuitry. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada389769.

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Zeng, Jian, Ali Toosi, Rohan L. Fernando, Jack C. M. Dekkers, and Dorian J. Garrick. Genomic Selection of Purebred Animals for Crossbred Performance in the Presence of Dominant Gene Action. Iowa State University, 2013. http://dx.doi.org/10.31274/ans_air-180814-1249.

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Dubcovsky, Jorge, Tzion Fahima, and Ann Blechl. Positional cloning of a gene responsible for high grain protein content in tetraploid wheat. United States Department of Agriculture, 2003. http://dx.doi.org/10.32747/2003.7695875.bard.

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High Grain Protein Content (GPC) is a desirable trait in breadmaking and pasta wheat varieties because of its positive effects on quality and nutritional value. However, selection for GPC is limited by our poor understanding of the genes involved in the accumulation of protein in the grain. The long-term goal of this project is to provide a better understanding of the genes controlling GPC in wheat. The specific objectives of this project were: a) to develop a high-density genetic map of the GPC gene in tetraploid wheat, b) to construct a T. turgidum Bacterial Artificial Chromosome (BAC) libra
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Suriyaphol, Gunnaporn. Study the gene expression of E-cadherin, syndecan1, matrix metalloproteinases-2, -7, -9, -14 and tissue inhibitors of metalloproteinases-1 and -2 in canine oral melanoma. Chulalongkorn University, 2015. https://doi.org/10.58837/chula.res.2015.80.

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The objectives of this study were to 1.) select the suitable reference genes for quantitative real-time polymerse chain reaction in the most common canine oral cancers: oral melanoma (OM) and oral squamous cell carcinoma (OSCC), 2.) study the gene expression of E-cadherin (CDH1), syndecan 1 (SDC1), matrix metalloproteinases-2, -7, -9, -14 (MMP2, MMP7, MMP9, MMP14) and tissue inhibitors of metalloproteinases-1 and -2 (TIMP1, TIMP2) in canine OM at the mRNA level and study the CDH1, SDC1 and Ki-67 protein expression by immunohistochemistry, and 3.) study the association of gene expression and th
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