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You searched for subject:(phenome). Showing records 1 – 12 of 12 total matches.

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King Abdullah University of Science and Technology

1. Ramaprasad, Abhinay. Phenomics, Genomics and Genetics in Plasmodium vinckei.

Degree: Biological and Environmental Sciences and Engineering (BESE) Division, 2017, King Abdullah University of Science and Technology

 Rodent malaria parasites (RMPs) serve as tractable models for experimental genetics, and as valuable tools to study malaria parasite biology and host-parasitevector interactions. Plasmodium vinckei,… (more)

Subjects/Keywords: Malaria; Plasmodium Vinckei; rodent malaria parasites; Genome; phenome; Transcriptome

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APA (6th Edition):

Ramaprasad, A. (2017). Phenomics, Genomics and Genetics in Plasmodium vinckei. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/626109

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ramaprasad, Abhinay. “Phenomics, Genomics and Genetics in Plasmodium vinckei.” 2017. Thesis, King Abdullah University of Science and Technology. Accessed April 10, 2021. http://hdl.handle.net/10754/626109.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ramaprasad, Abhinay. “Phenomics, Genomics and Genetics in Plasmodium vinckei.” 2017. Web. 10 Apr 2021.

Vancouver:

Ramaprasad A. Phenomics, Genomics and Genetics in Plasmodium vinckei. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2017. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/10754/626109.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ramaprasad A. Phenomics, Genomics and Genetics in Plasmodium vinckei. [Thesis]. King Abdullah University of Science and Technology; 2017. Available from: http://hdl.handle.net/10754/626109

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Vanderbilt University

2. Teixeira, Pedro Luis, Jr. Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data.

Degree: PhD, Biomedical Informatics, 2015, Vanderbilt University

 The aims of this project are 1) to evaluate various data sources and algorithms for identifying hypertensive individuals within the electronic health record, and 2)… (more)

Subjects/Keywords: biomedical informatics; phenome-wide association studies; hypertension; random forests; machine learning; natural language processing

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APA (6th Edition):

Teixeira, Pedro Luis, J. (2015). Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14022

Chicago Manual of Style (16th Edition):

Teixeira, Pedro Luis, Jr. “Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data.” 2015. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021. http://hdl.handle.net/1803/14022.

MLA Handbook (7th Edition):

Teixeira, Pedro Luis, Jr. “Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data.” 2015. Web. 10 Apr 2021.

Vancouver:

Teixeira, Pedro Luis J. Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data. [Internet] [Doctoral dissertation]. Vanderbilt University; 2015. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/1803/14022.

Council of Science Editors:

Teixeira, Pedro Luis J. Computational Phenotyping and Phenome-wide Association Studies: Leveraging Machine Learning and Natural Language Processing to Understand Electronic Health Record Data. [Doctoral Dissertation]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/14022


Penn State University

3. Hall, Molly Ann. Beyond genome-wide association studies (GWAS): Emerging methods for investigating complex associations for common traits.

Degree: 2015, Penn State University

 Genome-wide association studies (GWAS) have identified numerous loci associated with human phenotypes. This approach, however, does not consider the richly diverse and complex environment with… (more)

Subjects/Keywords: gene-gene interactions; epistasis; PheWAS; phenome; EWAS; exposome; gene-environment interactions; complex traits

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APA (6th Edition):

Hall, M. A. (2015). Beyond genome-wide association studies (GWAS): Emerging methods for investigating complex associations for common traits. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26751

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hall, Molly Ann. “Beyond genome-wide association studies (GWAS): Emerging methods for investigating complex associations for common traits.” 2015. Thesis, Penn State University. Accessed April 10, 2021. https://submit-etda.libraries.psu.edu/catalog/26751.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hall, Molly Ann. “Beyond genome-wide association studies (GWAS): Emerging methods for investigating complex associations for common traits.” 2015. Web. 10 Apr 2021.

Vancouver:

Hall MA. Beyond genome-wide association studies (GWAS): Emerging methods for investigating complex associations for common traits. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Apr 10]. Available from: https://submit-etda.libraries.psu.edu/catalog/26751.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hall MA. Beyond genome-wide association studies (GWAS): Emerging methods for investigating complex associations for common traits. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26751

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Cambridge

4. Moore, Rachel. Exploring Multivariate Gene-Environment Interactions: Models And Applications.

Degree: PhD, 2019, University of Cambridge

 Complex diseases are driven by multiple risk factors, including genetic variants, environmental exposures and interactions between the two. The advent of GWAS in 2005 and… (more)

Subjects/Keywords: Genetics; Gene-environment interactions; Phenome-wide association study; Genome-wide association study; Cardiometabolic traits; StructLMM

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APA (6th Edition):

Moore, R. (2019). Exploring Multivariate Gene-Environment Interactions: Models And Applications. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/290971

Chicago Manual of Style (16th Edition):

Moore, Rachel. “Exploring Multivariate Gene-Environment Interactions: Models And Applications.” 2019. Doctoral Dissertation, University of Cambridge. Accessed April 10, 2021. https://www.repository.cam.ac.uk/handle/1810/290971.

MLA Handbook (7th Edition):

Moore, Rachel. “Exploring Multivariate Gene-Environment Interactions: Models And Applications.” 2019. Web. 10 Apr 2021.

Vancouver:

Moore R. Exploring Multivariate Gene-Environment Interactions: Models And Applications. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2021 Apr 10]. Available from: https://www.repository.cam.ac.uk/handle/1810/290971.

Council of Science Editors:

Moore R. Exploring Multivariate Gene-Environment Interactions: Models And Applications. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/290971


University of Minnesota

5. Petegrosso, Raphael. Learning High-Order Relations for Network-Based Phenome-Genome Association Analysis.

Degree: PhD, Computer Science, 2019, University of Minnesota

 An organism's phenome is the expression of characteristics from genetic inheritance and interaction with the environment. This includes simple physical appearance and traits, and even… (more)

Subjects/Keywords: association analysis; biological networks; machine learning; phenome; phenotype prediction; remote homology detection

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APA (6th Edition):

Petegrosso, R. (2019). Learning High-Order Relations for Network-Based Phenome-Genome Association Analysis. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/209128

Chicago Manual of Style (16th Edition):

Petegrosso, Raphael. “Learning High-Order Relations for Network-Based Phenome-Genome Association Analysis.” 2019. Doctoral Dissertation, University of Minnesota. Accessed April 10, 2021. http://hdl.handle.net/11299/209128.

MLA Handbook (7th Edition):

Petegrosso, Raphael. “Learning High-Order Relations for Network-Based Phenome-Genome Association Analysis.” 2019. Web. 10 Apr 2021.

Vancouver:

Petegrosso R. Learning High-Order Relations for Network-Based Phenome-Genome Association Analysis. [Internet] [Doctoral dissertation]. University of Minnesota; 2019. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/11299/209128.

Council of Science Editors:

Petegrosso R. Learning High-Order Relations for Network-Based Phenome-Genome Association Analysis. [Doctoral Dissertation]. University of Minnesota; 2019. Available from: http://hdl.handle.net/11299/209128


University of Cambridge

6. Moore, Rachel. Exploring multivariate gene-environment interactions : models and applications.

Degree: PhD, 2019, University of Cambridge

 Complex diseases are driven by multiple risk factors, including genetic variants, environmental exposures and interactions between the two. The advent of GWAS in 2005 and… (more)

Subjects/Keywords: Genetics; Gene-environment interactions; Phenome-wide association study; Genome-wide association study; Cardiometabolic traits; StructLMM

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APA (6th Edition):

Moore, R. (2019). Exploring multivariate gene-environment interactions : models and applications. (Doctoral Dissertation). University of Cambridge. Retrieved from https://doi.org/10.17863/CAM.38150 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774660

Chicago Manual of Style (16th Edition):

Moore, Rachel. “Exploring multivariate gene-environment interactions : models and applications.” 2019. Doctoral Dissertation, University of Cambridge. Accessed April 10, 2021. https://doi.org/10.17863/CAM.38150 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774660.

MLA Handbook (7th Edition):

Moore, Rachel. “Exploring multivariate gene-environment interactions : models and applications.” 2019. Web. 10 Apr 2021.

Vancouver:

Moore R. Exploring multivariate gene-environment interactions : models and applications. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2021 Apr 10]. Available from: https://doi.org/10.17863/CAM.38150 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774660.

Council of Science Editors:

Moore R. Exploring multivariate gene-environment interactions : models and applications. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://doi.org/10.17863/CAM.38150 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.774660


University of Wisconsin – Milwaukee

7. Rastegar-Mojarad, Majid. Use of Text Data in Identifying and Prioritizing Potential Drug Repositioning Candidates.

Degree: PhD, Biomedical and Health Informatics, 2019, University of Wisconsin – Milwaukee

  New drug development costs between 500 million and 2 billion dollars and takes 10-15 years, with a success rate of less than 10%. Drug… (more)

Subjects/Keywords: Biomedical literature; Drug repositioning; Natural Language Processing; Phenome-Wide Association Studies; Social media; Text data; Computer Sciences

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APA (6th Edition):

Rastegar-Mojarad, M. (2019). Use of Text Data in Identifying and Prioritizing Potential Drug Repositioning Candidates. (Doctoral Dissertation). University of Wisconsin – Milwaukee. Retrieved from https://dc.uwm.edu/etd/2114

Chicago Manual of Style (16th Edition):

Rastegar-Mojarad, Majid. “Use of Text Data in Identifying and Prioritizing Potential Drug Repositioning Candidates.” 2019. Doctoral Dissertation, University of Wisconsin – Milwaukee. Accessed April 10, 2021. https://dc.uwm.edu/etd/2114.

MLA Handbook (7th Edition):

Rastegar-Mojarad, Majid. “Use of Text Data in Identifying and Prioritizing Potential Drug Repositioning Candidates.” 2019. Web. 10 Apr 2021.

Vancouver:

Rastegar-Mojarad M. Use of Text Data in Identifying and Prioritizing Potential Drug Repositioning Candidates. [Internet] [Doctoral dissertation]. University of Wisconsin – Milwaukee; 2019. [cited 2021 Apr 10]. Available from: https://dc.uwm.edu/etd/2114.

Council of Science Editors:

Rastegar-Mojarad M. Use of Text Data in Identifying and Prioritizing Potential Drug Repositioning Candidates. [Doctoral Dissertation]. University of Wisconsin – Milwaukee; 2019. Available from: https://dc.uwm.edu/etd/2114


Edith Cowan University

8. Li, Xingang. Heritability enrichment of immunoglobulin G N-glycosylation relevant genes in specific tissues.

Degree: 2020, Edith Cowan University

 Genome-wide association studies (GWAS) have identified over 60 genetic loci associated with IgG N-glycosylation; however, the causal genes and their abundance in relevant tissues are… (more)

Subjects/Keywords: Immunoglobulin G; N-glycosylation; transcriptome-wide association study; phenome-wide association study; Cell and Developmental Biology; Genetics and Genomics

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APA (6th Edition):

Li, X. (2020). Heritability enrichment of immunoglobulin G N-glycosylation relevant genes in specific tissues. (Thesis). Edith Cowan University. Retrieved from https://ro.ecu.edu.au/theses/2386

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Xingang. “Heritability enrichment of immunoglobulin G N-glycosylation relevant genes in specific tissues.” 2020. Thesis, Edith Cowan University. Accessed April 10, 2021. https://ro.ecu.edu.au/theses/2386.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Xingang. “Heritability enrichment of immunoglobulin G N-glycosylation relevant genes in specific tissues.” 2020. Web. 10 Apr 2021.

Vancouver:

Li X. Heritability enrichment of immunoglobulin G N-glycosylation relevant genes in specific tissues. [Internet] [Thesis]. Edith Cowan University; 2020. [cited 2021 Apr 10]. Available from: https://ro.ecu.edu.au/theses/2386.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li X. Heritability enrichment of immunoglobulin G N-glycosylation relevant genes in specific tissues. [Thesis]. Edith Cowan University; 2020. Available from: https://ro.ecu.edu.au/theses/2386

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Michigan Technological University

9. Zhu, Huanhuan. Statistical Methods for Analyzing Multivariate Phenotypes and Detecting Rare Variant Associations.

Degree: PhD, Department of Mathematical Sciences, 2018, Michigan Technological University

  This dissertation includes four papers with each distributed in one chapter. In chapter 1, I compared the performance of eight multivariate phenotype association tests.… (more)

Subjects/Keywords: Genome-wide association studies; multivariate phenotype association analysis; Phenome-wide association studies; Gene-based rare variant association analysis; Family-based designs; Biostatistics; Statistical Methodology; Statistical Models

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APA (6th Edition):

Zhu, H. (2018). Statistical Methods for Analyzing Multivariate Phenotypes and Detecting Rare Variant Associations. (Doctoral Dissertation). Michigan Technological University. Retrieved from https://digitalcommons.mtu.edu/etdr/638

Chicago Manual of Style (16th Edition):

Zhu, Huanhuan. “Statistical Methods for Analyzing Multivariate Phenotypes and Detecting Rare Variant Associations.” 2018. Doctoral Dissertation, Michigan Technological University. Accessed April 10, 2021. https://digitalcommons.mtu.edu/etdr/638.

MLA Handbook (7th Edition):

Zhu, Huanhuan. “Statistical Methods for Analyzing Multivariate Phenotypes and Detecting Rare Variant Associations.” 2018. Web. 10 Apr 2021.

Vancouver:

Zhu H. Statistical Methods for Analyzing Multivariate Phenotypes and Detecting Rare Variant Associations. [Internet] [Doctoral dissertation]. Michigan Technological University; 2018. [cited 2021 Apr 10]. Available from: https://digitalcommons.mtu.edu/etdr/638.

Council of Science Editors:

Zhu H. Statistical Methods for Analyzing Multivariate Phenotypes and Detecting Rare Variant Associations. [Doctoral Dissertation]. Michigan Technological University; 2018. Available from: https://digitalcommons.mtu.edu/etdr/638


Vanderbilt University

10. Bloodworth, Melissa Harintho. Regulation of Immune Responses during Airway Inflammation.

Degree: PhD, Microbiology and Immunology, 2017, Vanderbilt University

 Allergic asthma is refractory to corticosteroid treatment in up to 10% of patients and often leads to hospital admissions caused by respiratory viral and/ or… (more)

Subjects/Keywords: type 2 immunity (Th2); gamma-delta 17 (γδ17) cells; STAT6; Klebsiella pneumoniae; glucagon-like peptide 1 (GLP-1); respiratory syncytial virus (RSV); phenome-wide association study (PheWAS); regulatory T cells (Tregs); prostacyclin (PGI2)

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APA (6th Edition):

Bloodworth, M. H. (2017). Regulation of Immune Responses during Airway Inflammation. (Doctoral Dissertation). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/11246

Chicago Manual of Style (16th Edition):

Bloodworth, Melissa Harintho. “Regulation of Immune Responses during Airway Inflammation.” 2017. Doctoral Dissertation, Vanderbilt University. Accessed April 10, 2021. http://hdl.handle.net/1803/11246.

MLA Handbook (7th Edition):

Bloodworth, Melissa Harintho. “Regulation of Immune Responses during Airway Inflammation.” 2017. Web. 10 Apr 2021.

Vancouver:

Bloodworth MH. Regulation of Immune Responses during Airway Inflammation. [Internet] [Doctoral dissertation]. Vanderbilt University; 2017. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/1803/11246.

Council of Science Editors:

Bloodworth MH. Regulation of Immune Responses during Airway Inflammation. [Doctoral Dissertation]. Vanderbilt University; 2017. Available from: http://hdl.handle.net/1803/11246


University of Cincinnati

11. GUDIVADA, RANGA CHANDRA. DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION.

Degree: PhD, Engineering : Biomedical Engineering, 2007, University of Cincinnati

 An important goal for biomedical research is to elucidate causal and modifier networks of human disease. While integrative functional genomics approaches have shown success in… (more)

Subjects/Keywords: Semantic Web; RDF; OWL; SPARQL; Ontology; Biomedical Informatics; Bioinformatics; Integrative Bioinformatics; Text Mining; Phenome; Genome; Disease Modularity; Data Integration; Semantic Integration

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APA (6th Edition):

GUDIVADA, R. C. (2007). DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1195161740

Chicago Manual of Style (16th Edition):

GUDIVADA, RANGA CHANDRA. “DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION.” 2007. Doctoral Dissertation, University of Cincinnati. Accessed April 10, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1195161740.

MLA Handbook (7th Edition):

GUDIVADA, RANGA CHANDRA. “DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION.” 2007. Web. 10 Apr 2021.

Vancouver:

GUDIVADA RC. DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION. [Internet] [Doctoral dissertation]. University of Cincinnati; 2007. [cited 2021 Apr 10]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1195161740.

Council of Science Editors:

GUDIVADA RC. DISCOVERY AND PRIORITIZATION OF BIOLOGICAL ENTITIES UNDERLYING COMPLEX DISORDERS BY PHENOME-GENOME NETWORK INTEGRATION. [Doctoral Dissertation]. University of Cincinnati; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1195161740

12. Dey, Rounak. Statistical Methods for Analyzing Large Scale Biological Data.

Degree: PhD, Biostatistics, 2018, University of Michigan

 With the development of high-throughput biomedical technologies in recent years, the size of a typical biological dataset is increasing at a fast pace, especially in… (more)

Subjects/Keywords: High-Dimensional Data; Principal Component Analysis; Partial Least Squares; Genome-Wide Association Study; Phenome-Wide Association Study; Meta-Analysis; Genetics; Science (General); Statistics and Numeric Data; Science

…component analysis PheWAS phenome-wide association study PLS partial least squares QQ quantile… …phenome-wide association studies (GWASs or PheWASs) of the electronic health records… …association studies (GWASs) in phenome-wide scales (Hebbring, 2014; Verma et al… …problem of computational scalability in phenome-wide scale GWASs, and develop a single-variant… …phenome-wide association studies (PheWASs). Over the past decade, GWASs have… 

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APA (6th Edition):

Dey, R. (2018). Statistical Methods for Analyzing Large Scale Biological Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/146022

Chicago Manual of Style (16th Edition):

Dey, Rounak. “Statistical Methods for Analyzing Large Scale Biological Data.” 2018. Doctoral Dissertation, University of Michigan. Accessed April 10, 2021. http://hdl.handle.net/2027.42/146022.

MLA Handbook (7th Edition):

Dey, Rounak. “Statistical Methods for Analyzing Large Scale Biological Data.” 2018. Web. 10 Apr 2021.

Vancouver:

Dey R. Statistical Methods for Analyzing Large Scale Biological Data. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Apr 10]. Available from: http://hdl.handle.net/2027.42/146022.

Council of Science Editors:

Dey R. Statistical Methods for Analyzing Large Scale Biological Data. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/146022

.