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You searched for +publisher:"University of Washington" +contributor:("Thornton, Timothy A"). Showing records 1 – 7 of 7 total matches.

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University of Washington

1. Jia, Yichen. Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods.

Degree: 2017, University of Washington

 CYP3A4, one of the isozyme of the cytochromes P450 (CYPs), contributes significantly to drug clearance and drug-drug interactions. The goals of this project are to… (more)

Subjects/Keywords:

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Jia, Y. (2017). Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/40503

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):

Jia, Yichen. “Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods.” 2017. Thesis, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/40503.

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

MLA Handbook (7th Edition):

Jia, Yichen. “Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods.” 2017. Web. 09 May 2021.

Vancouver:

Jia Y. Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods. [Internet] [Thesis]. University of Washington; 2017. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/40503.

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

Council of Science Editors:

Jia Y. Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods. [Thesis]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/40503

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


University of Washington

2. Kirk, Jennifer Lee. Statistical Methods for Inferring Population Structure with Human Genome Sequence Data.

Degree: PhD, 2017, University of Washington

 Population structure is systematic variation in the human genome due to non-random mating because of physical or cultural barriers. Population structure is of interest in… (more)

Subjects/Keywords: Population Structure; Principal Components Analysis; Sequence Data; Statistical Genetics; Biostatistics; Genetics; Statistics; Biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kirk, J. L. (2017). Statistical Methods for Inferring Population Structure with Human Genome Sequence Data. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/38587

Chicago Manual of Style (16th Edition):

Kirk, Jennifer Lee. “Statistical Methods for Inferring Population Structure with Human Genome Sequence Data.” 2017. Doctoral Dissertation, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/38587.

MLA Handbook (7th Edition):

Kirk, Jennifer Lee. “Statistical Methods for Inferring Population Structure with Human Genome Sequence Data.” 2017. Web. 09 May 2021.

Vancouver:

Kirk JL. Statistical Methods for Inferring Population Structure with Human Genome Sequence Data. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/38587.

Council of Science Editors:

Kirk JL. Statistical Methods for Inferring Population Structure with Human Genome Sequence Data. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/38587


University of Washington

3. Brown, Lisa Anne. Statistical Methods in Admixture Mapping: Mixed Model Based Testing and Genome-wide Significance Thresholds.

Degree: PhD, 2017, University of Washington

 Genetic admixture occurs when two or more previously isolated populations combine to form an admixed population. The study of admixed populations can provide valuable insights… (more)

Subjects/Keywords: admixed populations; admixture; admixture mapping; ancestry; mixed models; population structure; Genetics; Epidemiology; biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Brown, L. A. (2017). Statistical Methods in Admixture Mapping: Mixed Model Based Testing and Genome-wide Significance Thresholds. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/38075

Chicago Manual of Style (16th Edition):

Brown, Lisa Anne. “Statistical Methods in Admixture Mapping: Mixed Model Based Testing and Genome-wide Significance Thresholds.” 2017. Doctoral Dissertation, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/38075.

MLA Handbook (7th Edition):

Brown, Lisa Anne. “Statistical Methods in Admixture Mapping: Mixed Model Based Testing and Genome-wide Significance Thresholds.” 2017. Web. 09 May 2021.

Vancouver:

Brown LA. Statistical Methods in Admixture Mapping: Mixed Model Based Testing and Genome-wide Significance Thresholds. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/38075.

Council of Science Editors:

Brown LA. Statistical Methods in Admixture Mapping: Mixed Model Based Testing and Genome-wide Significance Thresholds. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/38075

4. Conomos, Matthew Phillip. Inferring, Estimating, and Accounting for Population and Pedigree Structure in Genetic Analyses.

Degree: PhD, 2015, University of Washington

 Genetic studies of admixed individuals with ancestry derived from multiple previously isolated populations have become more common in recent years. Statistical methodology for analyzing genetic… (more)

Subjects/Keywords: admixture; genetic association testing; identity by descent; pedigree; population structure; relatedness; Biostatistics; Genetics; biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Conomos, M. P. (2015). Inferring, Estimating, and Accounting for Population and Pedigree Structure in Genetic Analyses. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/27424

Chicago Manual of Style (16th Edition):

Conomos, Matthew Phillip. “Inferring, Estimating, and Accounting for Population and Pedigree Structure in Genetic Analyses.” 2015. Doctoral Dissertation, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/27424.

MLA Handbook (7th Edition):

Conomos, Matthew Phillip. “Inferring, Estimating, and Accounting for Population and Pedigree Structure in Genetic Analyses.” 2015. Web. 09 May 2021.

Vancouver:

Conomos MP. Inferring, Estimating, and Accounting for Population and Pedigree Structure in Genetic Analyses. [Internet] [Doctoral dissertation]. University of Washington; 2015. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/27424.

Council of Science Editors:

Conomos MP. Inferring, Estimating, and Accounting for Population and Pedigree Structure in Genetic Analyses. [Doctoral Dissertation]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/27424

5. Willig, Laurel K. Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients.

Degree: 2013, University of Washington

 Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients Laurel K. Willig Timothy Thornton Background: Rates of acute kidney… (more)

Subjects/Keywords: acute kidney injury; association; genetic; hematopoietic stem cell transplant; polymorphism; Genetics; Medicine; public health genetics

University of Washington suggested that it might be related to AKI development in other populations… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Willig, L. K. (2013). Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/23654

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):

Willig, Laurel K. “Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients.” 2013. Thesis, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/23654.

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

MLA Handbook (7th Edition):

Willig, Laurel K. “Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients.” 2013. Web. 09 May 2021.

Vancouver:

Willig LK. Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients. [Internet] [Thesis]. University of Washington; 2013. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/23654.

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

Council of Science Editors:

Willig LK. Validation of single nucleotide polymorphisms associated with acute kidney injury in bone marrow transplant recipients. [Thesis]. University of Washington; 2013. Available from: http://hdl.handle.net/1773/23654

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

6. McHugh, Caitlin Patricia. Statistical Methods for the Analysis of Autosomal and X Chromosome Genetic Data in Samples with Unknown Structure.

Degree: PhD, 2016, University of Washington

 Genome-wide association studies (GWAS) and sequencing association studies are routinely conducted for the mapping of genes to complex traits. Genetic variants on the X chromosome… (more)

Subjects/Keywords: admixture; biostatistics; genome-wide association studies; rare variant association; statistical genetics; Biostatistics; Statistics; Genetics; biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

McHugh, C. P. (2016). Statistical Methods for the Analysis of Autosomal and X Chromosome Genetic Data in Samples with Unknown Structure. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/35981

Chicago Manual of Style (16th Edition):

McHugh, Caitlin Patricia. “Statistical Methods for the Analysis of Autosomal and X Chromosome Genetic Data in Samples with Unknown Structure.” 2016. Doctoral Dissertation, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/35981.

MLA Handbook (7th Edition):

McHugh, Caitlin Patricia. “Statistical Methods for the Analysis of Autosomal and X Chromosome Genetic Data in Samples with Unknown Structure.” 2016. Web. 09 May 2021.

Vancouver:

McHugh CP. Statistical Methods for the Analysis of Autosomal and X Chromosome Genetic Data in Samples with Unknown Structure. [Internet] [Doctoral dissertation]. University of Washington; 2016. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/35981.

Council of Science Editors:

McHugh CP. Statistical Methods for the Analysis of Autosomal and X Chromosome Genetic Data in Samples with Unknown Structure. [Doctoral Dissertation]. University of Washington; 2016. Available from: http://hdl.handle.net/1773/35981

7. Liu, Mingdong. A more powerful quasi-likelihood score test for detecting genetic association with multivariate phenotypes in related samples.

Degree: 2015, University of Washington

 Pleiotropy is a commonly observed phenomenon in human genetics where a single gene influences multiple, and sometimes seemingly unrelated traits. Recently there has been significant… (more)

Subjects/Keywords: Genetic association test; GWAS; multiple traits; quasi-likelihood score test; Biostatistics; biostatistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Liu, M. (2015). A more powerful quasi-likelihood score test for detecting genetic association with multivariate phenotypes in related samples. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/33618

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):

Liu, Mingdong. “A more powerful quasi-likelihood score test for detecting genetic association with multivariate phenotypes in related samples.” 2015. Thesis, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/33618.

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

MLA Handbook (7th Edition):

Liu, Mingdong. “A more powerful quasi-likelihood score test for detecting genetic association with multivariate phenotypes in related samples.” 2015. Web. 09 May 2021.

Vancouver:

Liu M. A more powerful quasi-likelihood score test for detecting genetic association with multivariate phenotypes in related samples. [Internet] [Thesis]. University of Washington; 2015. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/33618.

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

Council of Science Editors:

Liu M. A more powerful quasi-likelihood score test for detecting genetic association with multivariate phenotypes in related samples. [Thesis]. University of Washington; 2015. Available from: http://hdl.handle.net/1773/33618

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

.