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You searched for +publisher:"Georgia Tech" +contributor:("Jordan, I. King"). Showing records 1 – 16 of 16 total matches.

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Georgia Tech

1. Ravishankar, Shashidhar. Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species.

Degree: PhD, Biology, 2019, Georgia Tech

 The goal of this thesis is to develop algorithms for the analysis of P. falciparum, P. brasilianum, and P. malariae. Malaria is endemic in many… (more)

Subjects/Keywords: Bioinformatics; Variant calling; Consensus variant calling; Genomic clustering; Alignment free algorithms; k-mer based; Molecular surveillance; Malaria; Anti-malarial drug resistance

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APA (6th Edition):

Ravishankar, S. (2019). Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62281

Chicago Manual of Style (16th Edition):

Ravishankar, Shashidhar. “Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species.” 2019. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/62281.

MLA Handbook (7th Edition):

Ravishankar, Shashidhar. “Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species.” 2019. Web. 16 Jan 2021.

Vancouver:

Ravishankar S. Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/62281.

Council of Science Editors:

Ravishankar S. Genetic epidemiology algorithms for tracking drug resistance variants and genomic clustering of plasmodium species. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62281


Georgia Tech

2. Peng, Shengyun. Understanding virus-host interactions through single cell and whole genome analysis.

Degree: PhD, Biology, 2018, Georgia Tech

 Viruses and their microbial hosts are widely distributed in the environment, including in oceans, soils, fresh water, and even in extreme environments such as the… (more)

Subjects/Keywords: Virus; Virus ecology; Microbial ecology; Bioinformatics

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APA (6th Edition):

Peng, S. (2018). Understanding virus-host interactions through single cell and whole genome analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62229

Chicago Manual of Style (16th Edition):

Peng, Shengyun. “Understanding virus-host interactions through single cell and whole genome analysis.” 2018. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/62229.

MLA Handbook (7th Edition):

Peng, Shengyun. “Understanding virus-host interactions through single cell and whole genome analysis.” 2018. Web. 16 Jan 2021.

Vancouver:

Peng S. Understanding virus-host interactions through single cell and whole genome analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/62229.

Council of Science Editors:

Peng S. Understanding virus-host interactions through single cell and whole genome analysis. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62229


Georgia Tech

3. Norris, Emily Taylor. Human genetic ancestry, health, and adaptation in Latin America.

Degree: PhD, Biology, 2019, Georgia Tech

 Genetic admixture is the process that occurs when populations that were previously reproductively isolated, and consequently genetically diverged, come back together and exchange genes. Recent… (more)

Subjects/Keywords: Population genomics; Admixture; Genetic ancestry; Admixture-enabled selection; Assortative mating; Polygenic phenotypes; Rapid adaptive evolution; Mate choice

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APA (6th Edition):

Norris, E. T. (2019). Human genetic ancestry, health, and adaptation in Latin America. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62320

Chicago Manual of Style (16th Edition):

Norris, Emily Taylor. “Human genetic ancestry, health, and adaptation in Latin America.” 2019. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/62320.

MLA Handbook (7th Edition):

Norris, Emily Taylor. “Human genetic ancestry, health, and adaptation in Latin America.” 2019. Web. 16 Jan 2021.

Vancouver:

Norris ET. Human genetic ancestry, health, and adaptation in Latin America. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/62320.

Council of Science Editors:

Norris ET. Human genetic ancestry, health, and adaptation in Latin America. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62320


Georgia Tech

4. Srinivasan, Swetha. Understanding the systemic roles of exosomes in innate immunity.

Degree: PhD, Biology, 2016, Georgia Tech

 Cell-cell communication is critical for rapidly spreading the message of infection and enabling the innate immune system to mount a broad response against the pathogen.… (more)

Subjects/Keywords: Exosomes; Lymphatic transport; TLR; LPS; Poly (I:C) macrophages; Innate immunity

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APA (6th Edition):

Srinivasan, S. (2016). Understanding the systemic roles of exosomes in innate immunity. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58595

Chicago Manual of Style (16th Edition):

Srinivasan, Swetha. “Understanding the systemic roles of exosomes in innate immunity.” 2016. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/58595.

MLA Handbook (7th Edition):

Srinivasan, Swetha. “Understanding the systemic roles of exosomes in innate immunity.” 2016. Web. 16 Jan 2021.

Vancouver:

Srinivasan S. Understanding the systemic roles of exosomes in innate immunity. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/58595.

Council of Science Editors:

Srinivasan S. Understanding the systemic roles of exosomes in innate immunity. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/58595


Georgia Tech

5. Zhao, Ziming. Exploiting phylogenetics to understand genome evolution in both modern and ancestral organisms.

Degree: PhD, Biology, 2012, Georgia Tech

 Computational evolutionary analyses, particularly phylogenetics and ancestral reconstruction, have been extensively exploited under different algorithms and evolutionary models to better understand genome evolution from both… (more)

Subjects/Keywords: 3-isopropylmalate dehydrogenase; Catenin; Mycoplasma; Bioinformatics; Molecular evolution; Paleoenvironment; Synthetic genome; Avian influenza virus; Minimal genome; Phylogeny; Evolution (Biology); Bioinformatics

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APA (6th Edition):

Zhao, Z. (2012). Exploiting phylogenetics to understand genome evolution in both modern and ancestral organisms. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/48988

Chicago Manual of Style (16th Edition):

Zhao, Ziming. “Exploiting phylogenetics to understand genome evolution in both modern and ancestral organisms.” 2012. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/48988.

MLA Handbook (7th Edition):

Zhao, Ziming. “Exploiting phylogenetics to understand genome evolution in both modern and ancestral organisms.” 2012. Web. 16 Jan 2021.

Vancouver:

Zhao Z. Exploiting phylogenetics to understand genome evolution in both modern and ancestral organisms. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/48988.

Council of Science Editors:

Zhao Z. Exploiting phylogenetics to understand genome evolution in both modern and ancestral organisms. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/48988


Georgia Tech

6. Rishishwar, Lavanya. Population genomics of human polymorphic transposable elements.

Degree: PhD, Biology, 2016, Georgia Tech

 Transposable element (TE) activity has had a major impact on the human genome; more than two-thirds of the sequence is derived from TE insertions. Several… (more)

Subjects/Keywords: Bioinformatics; Evolution; Natural selection; Human ancestry and admixture

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APA (6th Edition):

Rishishwar, L. (2016). Population genomics of human polymorphic transposable elements. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56323

Chicago Manual of Style (16th Edition):

Rishishwar, Lavanya. “Population genomics of human polymorphic transposable elements.” 2016. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/56323.

MLA Handbook (7th Edition):

Rishishwar, Lavanya. “Population genomics of human polymorphic transposable elements.” 2016. Web. 16 Jan 2021.

Vancouver:

Rishishwar L. Population genomics of human polymorphic transposable elements. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/56323.

Council of Science Editors:

Rishishwar L. Population genomics of human polymorphic transposable elements. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56323

7. Caro Quintero, Alejandro. The role of horizontal gene transfer in bacterial evolution.

Degree: PhD, Biology, 2013, Georgia Tech

 Horizontal gene transfer (HGT) is probably the most important mechanism for functional novelty and adaption in bacteria. However, a robust understanding of the rates of… (more)

Subjects/Keywords: Evolution; Bacteria; HGT; Gene transfer; Homologous recombination; Inter-phylum; Transgenic organisms; Genetic transformation; Bacteria; Bioinformatics; Adaptation (Biology)

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APA (6th Edition):

Caro Quintero, A. (2013). The role of horizontal gene transfer in bacterial evolution. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/48979

Chicago Manual of Style (16th Edition):

Caro Quintero, Alejandro. “The role of horizontal gene transfer in bacterial evolution.” 2013. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/48979.

MLA Handbook (7th Edition):

Caro Quintero, Alejandro. “The role of horizontal gene transfer in bacterial evolution.” 2013. Web. 16 Jan 2021.

Vancouver:

Caro Quintero A. The role of horizontal gene transfer in bacterial evolution. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/48979.

Council of Science Editors:

Caro Quintero A. The role of horizontal gene transfer in bacterial evolution. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/48979

8. Wang, Jianrong. Computational algorithm development for epigenomic analysis.

Degree: PhD, Biology, 2012, Georgia Tech

 Multiple computational algorithms were developed for analyzing ChIP-seq datasets of histone modifications. For basic ChIP-seq data processing, the problems of ambiguous short sequence read mapping… (more)

Subjects/Keywords: ChIP-seq; Histone modifications; Bioinformatics; Epigenetics; Insulators; Algorithms; Bioinformatics; Genetics Data processing; Epigenesis

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APA (6th Edition):

Wang, J. (2012). Computational algorithm development for epigenomic analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/48984

Chicago Manual of Style (16th Edition):

Wang, Jianrong. “Computational algorithm development for epigenomic analysis.” 2012. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/48984.

MLA Handbook (7th Edition):

Wang, Jianrong. “Computational algorithm development for epigenomic analysis.” 2012. Web. 16 Jan 2021.

Vancouver:

Wang J. Computational algorithm development for epigenomic analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/48984.

Council of Science Editors:

Wang J. Computational algorithm development for epigenomic analysis. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/48984

9. Jjingo, Daudi. Effects of repetitive DNA and epigenetics on human genome regulation.

Degree: PhD, Biology, 2013, Georgia Tech

 The highly developed and specialized anatomical and physiological characteristics observed for eukaryotes in general and mammals in particular are underwritten by an elaborate and intricate… (more)

Subjects/Keywords: Transcription; Gene expression; Epigenetics; Human genome; DNA; Genomics; Bioinformatics

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APA (6th Edition):

Jjingo, D. (2013). Effects of repetitive DNA and epigenetics on human genome regulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49120

Chicago Manual of Style (16th Edition):

Jjingo, Daudi. “Effects of repetitive DNA and epigenetics on human genome regulation.” 2013. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/49120.

MLA Handbook (7th Edition):

Jjingo, Daudi. “Effects of repetitive DNA and epigenetics on human genome regulation.” 2013. Web. 16 Jan 2021.

Vancouver:

Jjingo D. Effects of repetitive DNA and epigenetics on human genome regulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/49120.

Council of Science Editors:

Jjingo D. Effects of repetitive DNA and epigenetics on human genome regulation. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49120

10. Burns, Paul D. Gene finding in eukaryotic genomes using external information and machine learning techniques.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2013, Georgia Tech

 Gene finding in eukaryotic genomes is an essential part of a comprehensive approach to modern systems biology. Most methods developed in the past rely on… (more)

Subjects/Keywords: Gene finding; RNA-seq; Machine learning; SVM; Genomics; Eukaryotic cells; Gene mapping; Machine learning; Nucleotide sequence

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APA (6th Edition):

Burns, P. D. (2013). Gene finding in eukaryotic genomes using external information and machine learning techniques. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49023

Chicago Manual of Style (16th Edition):

Burns, Paul D. “Gene finding in eukaryotic genomes using external information and machine learning techniques.” 2013. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/49023.

MLA Handbook (7th Edition):

Burns, Paul D. “Gene finding in eukaryotic genomes using external information and machine learning techniques.” 2013. Web. 16 Jan 2021.

Vancouver:

Burns PD. Gene finding in eukaryotic genomes using external information and machine learning techniques. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/49023.

Council of Science Editors:

Burns PD. Gene finding in eukaryotic genomes using external information and machine learning techniques. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49023


Georgia Tech

11. Wang, Lu. Transposable element polymorphisms and human genome regulation.

Degree: PhD, Biology, 2017, Georgia Tech

 Transposable elements (TEs) are DNA sequences that are capable of moving from one genomic location to another. A large proportion of the human genome is… (more)

Subjects/Keywords: Transposable elements; Bioinformatics; Alu; L1; SVA; Gene expression; Gene regulation; GWAS; Expression quantitative trait loci; Polymorphism; Genetic variation

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APA (6th Edition):

Wang, L. (2017). Transposable element polymorphisms and human genome regulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59266

Chicago Manual of Style (16th Edition):

Wang, Lu. “Transposable element polymorphisms and human genome regulation.” 2017. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/59266.

MLA Handbook (7th Edition):

Wang, Lu. “Transposable element polymorphisms and human genome regulation.” 2017. Web. 16 Jan 2021.

Vancouver:

Wang L. Transposable element polymorphisms and human genome regulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/59266.

Council of Science Editors:

Wang L. Transposable element polymorphisms and human genome regulation. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59266

12. Conley, Andrew Berton. Alteration of transcription by non-coding elements in the human genome.

Degree: PhD, Biology, 2012, Georgia Tech

 The human genome contains ~1.5% coding sequence, with the remaining 98.5% being non-coding. The functional potential of the majority of this non-coding sequence remains unknown.… (more)

Subjects/Keywords: Gene regulation; Human genomics; Antisense transcription; Chromatin; Transposable elements; Functional genomics; Human genome; Human gene mapping; Gene mapping

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APA (6th Edition):

Conley, A. B. (2012). Alteration of transcription by non-coding elements in the human genome. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/44838

Chicago Manual of Style (16th Edition):

Conley, Andrew Berton. “Alteration of transcription by non-coding elements in the human genome.” 2012. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/44838.

MLA Handbook (7th Edition):

Conley, Andrew Berton. “Alteration of transcription by non-coding elements in the human genome.” 2012. Web. 16 Jan 2021.

Vancouver:

Conley AB. Alteration of transcription by non-coding elements in the human genome. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/44838.

Council of Science Editors:

Conley AB. Alteration of transcription by non-coding elements in the human genome. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/44838

13. Katz, Lee Scott. Computational tools for molecular epidemiology and computational genomics of Neisseria meningitidis.

Degree: PhD, Biology, 2010, Georgia Tech

 Neisseria meningitidis is a gram negative, and sometimes encapsulated, diplococcus that causes devastating disease worldwide. For the worldwide genetic surveillance of N. meningitidis, the gold… (more)

Subjects/Keywords: Meningitis; SNP; Genome; Typing; Recombination; Iinfluenza; Bioinformatics; Applied bioinformatics; Serogroup; ST; Sequencing projects; MLST; Epidemiology; Molecular epidemiology; Genomes; Genomics

Page 1

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APA (6th Edition):

Katz, L. S. (2010). Computational tools for molecular epidemiology and computational genomics of Neisseria meningitidis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42934

Chicago Manual of Style (16th Edition):

Katz, Lee Scott. “Computational tools for molecular epidemiology and computational genomics of Neisseria meningitidis.” 2010. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/42934.

MLA Handbook (7th Edition):

Katz, Lee Scott. “Computational tools for molecular epidemiology and computational genomics of Neisseria meningitidis.” 2010. Web. 16 Jan 2021.

Vancouver:

Katz LS. Computational tools for molecular epidemiology and computational genomics of Neisseria meningitidis. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/42934.

Council of Science Editors:

Katz LS. Computational tools for molecular epidemiology and computational genomics of Neisseria meningitidis. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/42934

14. Kislyuk, Andrey O. Algorithm development for next generation sequencing-based metagenome analysis.

Degree: PhD, Biology, 2010, Georgia Tech

 We present research on the design, development and application of algorithms for DNA sequence analysis, with a focus on environmental DNA (metagenomes). We present an… (more)

Subjects/Keywords: Metagenomics; DNA; Bioinformatics; Markov processes; Algorithms; Nucleotide sequence; Nucleotides Analysis

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APA (6th Edition):

Kislyuk, A. O. (2010). Algorithm development for next generation sequencing-based metagenome analysis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/42779

Chicago Manual of Style (16th Edition):

Kislyuk, Andrey O. “Algorithm development for next generation sequencing-based metagenome analysis.” 2010. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/42779.

MLA Handbook (7th Edition):

Kislyuk, Andrey O. “Algorithm development for next generation sequencing-based metagenome analysis.” 2010. Web. 16 Jan 2021.

Vancouver:

Kislyuk AO. Algorithm development for next generation sequencing-based metagenome analysis. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/42779.

Council of Science Editors:

Kislyuk AO. Algorithm development for next generation sequencing-based metagenome analysis. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/42779

15. Hunt, Brendan G. Molecular evolution in the social insects.

Degree: PhD, Biology, 2011, Georgia Tech

 Social insects are ecologically dominant because of their specialized, cooperative castes. Reproductive queens lay eggs, while workers take part in brood rearing, nest defense, and… (more)

Subjects/Keywords: Eusociality; Comparative genomics; Molecular genetics; Genomics; Insect societies; Insects Behavior

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APA (6th Edition):

Hunt, B. G. (2011). Molecular evolution in the social insects. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/43655

Chicago Manual of Style (16th Edition):

Hunt, Brendan G. “Molecular evolution in the social insects.” 2011. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/43655.

MLA Handbook (7th Edition):

Hunt, Brendan G. “Molecular evolution in the social insects.” 2011. Web. 16 Jan 2021.

Vancouver:

Hunt BG. Molecular evolution in the social insects. [Internet] [Doctoral dissertation]. Georgia Tech; 2011. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/43655.

Council of Science Editors:

Hunt BG. Molecular evolution in the social insects. [Doctoral Dissertation]. Georgia Tech; 2011. Available from: http://hdl.handle.net/1853/43655

16. Piriyapongsa, Jittima. Origin and evolution of eukaryotic gene sequences derived from transposable elements.

Degree: PhD, Biology, 2008, Georgia Tech

 My dissertation encompasses five different studies that are linked by a common theme the investigation of transposable element (TE) contributions to eukaryotic gene sequences. A… (more)

Subjects/Keywords: Transposable element; Evolution; Gene; Exonization; MITE; MiRNA; SiRNA; Transposons; Mobile genetic elements; Amino acid sequence

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APA (6th Edition):

Piriyapongsa, J. (2008). Origin and evolution of eukaryotic gene sequences derived from transposable elements. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/24766

Chicago Manual of Style (16th Edition):

Piriyapongsa, Jittima. “Origin and evolution of eukaryotic gene sequences derived from transposable elements.” 2008. Doctoral Dissertation, Georgia Tech. Accessed January 16, 2021. http://hdl.handle.net/1853/24766.

MLA Handbook (7th Edition):

Piriyapongsa, Jittima. “Origin and evolution of eukaryotic gene sequences derived from transposable elements.” 2008. Web. 16 Jan 2021.

Vancouver:

Piriyapongsa J. Origin and evolution of eukaryotic gene sequences derived from transposable elements. [Internet] [Doctoral dissertation]. Georgia Tech; 2008. [cited 2021 Jan 16]. Available from: http://hdl.handle.net/1853/24766.

Council of Science Editors:

Piriyapongsa J. Origin and evolution of eukaryotic gene sequences derived from transposable elements. [Doctoral Dissertation]. Georgia Tech; 2008. Available from: http://hdl.handle.net/1853/24766

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