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You searched for subject:(Gene expression Statistical methods ). Showing records 1 – 30 of 41246 total matches.

[1] [2] [3] [4] [5] … [1375]

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Oregon State University

1. Zhuo, Bin. Higher-level Analysis of RNA-Seq Experiment: Multiple Data Sets and Multiple Genes.

Degree: PhD, Statistics, 2016, Oregon State University

 Differential expression (DE) analysis is a key task in gene expression study, because it uncovers the association between expression levels of a gene and the… (more)

Subjects/Keywords: RNA-Seq; Gene expression  – Statistical methods

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APA (6th Edition):

Zhuo, B. (2016). Higher-level Analysis of RNA-Seq Experiment: Multiple Data Sets and Multiple Genes. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/59543

Chicago Manual of Style (16th Edition):

Zhuo, Bin. “Higher-level Analysis of RNA-Seq Experiment: Multiple Data Sets and Multiple Genes.” 2016. Doctoral Dissertation, Oregon State University. Accessed November 21, 2019. http://hdl.handle.net/1957/59543.

MLA Handbook (7th Edition):

Zhuo, Bin. “Higher-level Analysis of RNA-Seq Experiment: Multiple Data Sets and Multiple Genes.” 2016. Web. 21 Nov 2019.

Vancouver:

Zhuo B. Higher-level Analysis of RNA-Seq Experiment: Multiple Data Sets and Multiple Genes. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/1957/59543.

Council of Science Editors:

Zhuo B. Higher-level Analysis of RNA-Seq Experiment: Multiple Data Sets and Multiple Genes. [Doctoral Dissertation]. Oregon State University; 2016. Available from: http://hdl.handle.net/1957/59543


University of Hong Kong

2. Ai, Ni. A novel framework for expression quantitative trait loci mapping.

Degree: M. Phil., 2011, University of Hong Kong

published_or_final_version

Electrical and Electronic Engineering

Master

Master of Philosophy

Advisors/Committee Members: Hung, YS, Chang, C.

Subjects/Keywords: Gene expression - Statistical methods.; Quantitative genetics.

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APA (6th Edition):

Ai, N. (2011). A novel framework for expression quantitative trait loci mapping. (Masters Thesis). University of Hong Kong. Retrieved from Ai, N. [艾妮]. (2011). A novel framework for expression quantitative trait loci mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4715214 ; http://dx.doi.org/10.5353/th_b4715214 ; http://hdl.handle.net/10722/145695

Chicago Manual of Style (16th Edition):

Ai, Ni. “A novel framework for expression quantitative trait loci mapping.” 2011. Masters Thesis, University of Hong Kong. Accessed November 21, 2019. Ai, N. [艾妮]. (2011). A novel framework for expression quantitative trait loci mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4715214 ; http://dx.doi.org/10.5353/th_b4715214 ; http://hdl.handle.net/10722/145695.

MLA Handbook (7th Edition):

Ai, Ni. “A novel framework for expression quantitative trait loci mapping.” 2011. Web. 21 Nov 2019.

Vancouver:

Ai N. A novel framework for expression quantitative trait loci mapping. [Internet] [Masters thesis]. University of Hong Kong; 2011. [cited 2019 Nov 21]. Available from: Ai, N. [艾妮]. (2011). A novel framework for expression quantitative trait loci mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4715214 ; http://dx.doi.org/10.5353/th_b4715214 ; http://hdl.handle.net/10722/145695.

Council of Science Editors:

Ai N. A novel framework for expression quantitative trait loci mapping. [Masters Thesis]. University of Hong Kong; 2011. Available from: Ai, N. [艾妮]. (2011). A novel framework for expression quantitative trait loci mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4715214 ; http://dx.doi.org/10.5353/th_b4715214 ; http://hdl.handle.net/10722/145695

3. Farazi, Md Manzur Rahman. Identification of outliers in gene expression data.

Degree: Thesis (M.S.), 2015, Ball State University

 This work reports the application of techniques that proved useful in analyzing a large gene expression data set. Because it appears likely that genomic instability… (more)

Subjects/Keywords: Outliers (Statistics); Gene expression  – Statistical methods.; Cancer  – Genetic aspects  – Statistical methods.

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APA (6th Edition):

Farazi, M. M. R. (2015). Identification of outliers in gene expression data. (Masters Thesis). Ball State University. Retrieved from http://cardinalscholar.bsu.edu/handle/123456789/199559

Chicago Manual of Style (16th Edition):

Farazi, Md Manzur Rahman. “Identification of outliers in gene expression data.” 2015. Masters Thesis, Ball State University. Accessed November 21, 2019. http://cardinalscholar.bsu.edu/handle/123456789/199559.

MLA Handbook (7th Edition):

Farazi, Md Manzur Rahman. “Identification of outliers in gene expression data.” 2015. Web. 21 Nov 2019.

Vancouver:

Farazi MMR. Identification of outliers in gene expression data. [Internet] [Masters thesis]. Ball State University; 2015. [cited 2019 Nov 21]. Available from: http://cardinalscholar.bsu.edu/handle/123456789/199559.

Council of Science Editors:

Farazi MMR. Identification of outliers in gene expression data. [Masters Thesis]. Ball State University; 2015. Available from: http://cardinalscholar.bsu.edu/handle/123456789/199559


University of Missouri – Columbia

4. Qi, Yue. Equivalence test of high dimensional microarray data.

Degree: 2014, University of Missouri – Columbia

 [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The Booth lab at the University of Missouri has selectively-bred Wistar rats for low (LVR)… (more)

Subjects/Keywords: DNA microarrays  – Statistical methods; Gene expression  – Mathematical models

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APA (6th Edition):

Qi, Y. (2014). Equivalence test of high dimensional microarray data. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/45860

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):

Qi, Yue. “Equivalence test of high dimensional microarray data.” 2014. Thesis, University of Missouri – Columbia. Accessed November 21, 2019. http://hdl.handle.net/10355/45860.

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

MLA Handbook (7th Edition):

Qi, Yue. “Equivalence test of high dimensional microarray data.” 2014. Web. 21 Nov 2019.

Vancouver:

Qi Y. Equivalence test of high dimensional microarray data. [Internet] [Thesis]. University of Missouri – Columbia; 2014. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/10355/45860.

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

Council of Science Editors:

Qi Y. Equivalence test of high dimensional microarray data. [Thesis]. University of Missouri – Columbia; 2014. Available from: http://hdl.handle.net/10355/45860

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


Rutgers University

5. Dong, Qian, 1975-. Comparisons of statistical methods for determining gene expression signatures to predict binary cancer response.

Degree: Public Health, 2014, Rutgers University

Subjects/Keywords: Statistical methods; Gene expression – Statistical methods; Cancer – Genetic aspects

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

APA (6th Edition):

Dong, Qian, 1. (2014). Comparisons of statistical methods for determining gene expression signatures to predict binary cancer response. (Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45689/

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):

Dong, Qian, 1975-. “Comparisons of statistical methods for determining gene expression signatures to predict binary cancer response.” 2014. Thesis, Rutgers University. Accessed November 21, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/45689/.

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

MLA Handbook (7th Edition):

Dong, Qian, 1975-. “Comparisons of statistical methods for determining gene expression signatures to predict binary cancer response.” 2014. Web. 21 Nov 2019.

Vancouver:

Dong, Qian 1. Comparisons of statistical methods for determining gene expression signatures to predict binary cancer response. [Internet] [Thesis]. Rutgers University; 2014. [cited 2019 Nov 21]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45689/.

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

Council of Science Editors:

Dong, Qian 1. Comparisons of statistical methods for determining gene expression signatures to predict binary cancer response. [Thesis]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45689/

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


University of Hong Kong

6. Tam, Hak-fui. A Granger causality approach to gene regulatory network reconstructionbased on data from multiple experiments.

Degree: PhD, 2012, University of Hong Kong

The discovery of gene regulatory network (GRN) using gene expression data is one of the promising directions for deciphering biological mechanisms, which underlie many basic… (more)

Subjects/Keywords: Gene regulatory networks - Statistical methods.

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APA (6th Edition):

Tam, H. (2012). A Granger causality approach to gene regulatory network reconstructionbased on data from multiple experiments. (Doctoral Dissertation). University of Hong Kong. Retrieved from http://hdl.handle.net/10722/180988

Chicago Manual of Style (16th Edition):

Tam, Hak-fui. “A Granger causality approach to gene regulatory network reconstructionbased on data from multiple experiments.” 2012. Doctoral Dissertation, University of Hong Kong. Accessed November 21, 2019. http://hdl.handle.net/10722/180988.

MLA Handbook (7th Edition):

Tam, Hak-fui. “A Granger causality approach to gene regulatory network reconstructionbased on data from multiple experiments.” 2012. Web. 21 Nov 2019.

Vancouver:

Tam H. A Granger causality approach to gene regulatory network reconstructionbased on data from multiple experiments. [Internet] [Doctoral dissertation]. University of Hong Kong; 2012. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/10722/180988.

Council of Science Editors:

Tam H. A Granger causality approach to gene regulatory network reconstructionbased on data from multiple experiments. [Doctoral Dissertation]. University of Hong Kong; 2012. Available from: http://hdl.handle.net/10722/180988


Macquarie University

7. Peters, Timothy John. Protocols for dimension reduction of transcriptomic data.

Degree: PhD, 2012, Macquarie University

Thesis by publication.

Bibliography: p. [147]-162.

1. Biological background and introduction  – 2. The evolution of dimension reduction techniques  – 3. Two-step cross-entropy feature selection… (more)

Subjects/Keywords: Bioinformatics; Systems biology; Gene expression  – Mathematical models; Gene expression  – Statistical methods; Lymphomas  – Mathematical models; Cancer  – Mathematical models; Data mining  – Statistical methods; Data reduction; bioinformatics; dimension reduction; gene expression profiling; lymphoma; feature selection

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APA (6th Edition):

Peters, T. J. (2012). Protocols for dimension reduction of transcriptomic data. (Doctoral Dissertation). Macquarie University. Retrieved from http://hdl.handle.net/1959.14/224712

Chicago Manual of Style (16th Edition):

Peters, Timothy John. “Protocols for dimension reduction of transcriptomic data.” 2012. Doctoral Dissertation, Macquarie University. Accessed November 21, 2019. http://hdl.handle.net/1959.14/224712.

MLA Handbook (7th Edition):

Peters, Timothy John. “Protocols for dimension reduction of transcriptomic data.” 2012. Web. 21 Nov 2019.

Vancouver:

Peters TJ. Protocols for dimension reduction of transcriptomic data. [Internet] [Doctoral dissertation]. Macquarie University; 2012. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/1959.14/224712.

Council of Science Editors:

Peters TJ. Protocols for dimension reduction of transcriptomic data. [Doctoral Dissertation]. Macquarie University; 2012. Available from: http://hdl.handle.net/1959.14/224712


Michigan State University

8. Desai, Keyur Hemantkumar. Dependency and purity in large-scale statistical significance testing : a DNA microarray perspective.

Degree: PhD, Electrical Engineering, 2008, Michigan State University

Subjects/Keywords: Gene expression – Research – Statistical methods; DNA microarrays – Research – Statistical methods

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

APA (6th Edition):

Desai, K. H. (2008). Dependency and purity in large-scale statistical significance testing : a DNA microarray perspective. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:39405

Chicago Manual of Style (16th Edition):

Desai, Keyur Hemantkumar. “Dependency and purity in large-scale statistical significance testing : a DNA microarray perspective.” 2008. Doctoral Dissertation, Michigan State University. Accessed November 21, 2019. http://etd.lib.msu.edu/islandora/object/etd:39405.

MLA Handbook (7th Edition):

Desai, Keyur Hemantkumar. “Dependency and purity in large-scale statistical significance testing : a DNA microarray perspective.” 2008. Web. 21 Nov 2019.

Vancouver:

Desai KH. Dependency and purity in large-scale statistical significance testing : a DNA microarray perspective. [Internet] [Doctoral dissertation]. Michigan State University; 2008. [cited 2019 Nov 21]. Available from: http://etd.lib.msu.edu/islandora/object/etd:39405.

Council of Science Editors:

Desai KH. Dependency and purity in large-scale statistical significance testing : a DNA microarray perspective. [Doctoral Dissertation]. Michigan State University; 2008. Available from: http://etd.lib.msu.edu/islandora/object/etd:39405

9. Yang, Celeste. A Study Of Multi-Group And Multivariate Tests Of Equivalence With Application To Microarray And.

Degree: 2013, University of Alabama – Birmingham

In this dissertation we have adapted two multi-group equivalence tests to be performed on high-dimensional data. The F and Range test for multi-group equivalence were… (more)

Subjects/Keywords: DNA microarrays – Statistical methods. Multivariate analysis. Gene expression – Computer simulation. Statistical hypothesis testing. Equivalence classes (Set theory)

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APA (6th Edition):

Yang, C. (2013). A Study Of Multi-Group And Multivariate Tests Of Equivalence With Application To Microarray And. (Thesis). University of Alabama – Birmingham. Retrieved from http://contentdm.mhsl.uab.edu/u?/etd,1753

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):

Yang, Celeste. “A Study Of Multi-Group And Multivariate Tests Of Equivalence With Application To Microarray And.” 2013. Thesis, University of Alabama – Birmingham. Accessed November 21, 2019. http://contentdm.mhsl.uab.edu/u?/etd,1753.

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

MLA Handbook (7th Edition):

Yang, Celeste. “A Study Of Multi-Group And Multivariate Tests Of Equivalence With Application To Microarray And.” 2013. Web. 21 Nov 2019.

Vancouver:

Yang C. A Study Of Multi-Group And Multivariate Tests Of Equivalence With Application To Microarray And. [Internet] [Thesis]. University of Alabama – Birmingham; 2013. [cited 2019 Nov 21]. Available from: http://contentdm.mhsl.uab.edu/u?/etd,1753.

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

Council of Science Editors:

Yang C. A Study Of Multi-Group And Multivariate Tests Of Equivalence With Application To Microarray And. [Thesis]. University of Alabama – Birmingham; 2013. Available from: http://contentdm.mhsl.uab.edu/u?/etd,1753

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

10. Beer, Joanne C. Power and sample size determination for time course microarray differential expression studies : a positive false discovery rate and permutation-based simulation method.

Degree: M.P.H., 2013, Oregon Health Sciences University

Subjects/Keywords: Gene expression  – Statistical methods; DNA microarrays; Sample Size; Microarray Analysis; Statistics as Topic

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APA (6th Edition):

Beer, J. C. (2013). Power and sample size determination for time course microarray differential expression studies : a positive false discovery rate and permutation-based simulation method. (Thesis). Oregon Health Sciences University. Retrieved from doi:10.6083/M4BK19D8 ; http://digitalcommons.ohsu.edu/etd/957

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):

Beer, Joanne C. “Power and sample size determination for time course microarray differential expression studies : a positive false discovery rate and permutation-based simulation method.” 2013. Thesis, Oregon Health Sciences University. Accessed November 21, 2019. doi:10.6083/M4BK19D8 ; http://digitalcommons.ohsu.edu/etd/957.

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

MLA Handbook (7th Edition):

Beer, Joanne C. “Power and sample size determination for time course microarray differential expression studies : a positive false discovery rate and permutation-based simulation method.” 2013. Web. 21 Nov 2019.

Vancouver:

Beer JC. Power and sample size determination for time course microarray differential expression studies : a positive false discovery rate and permutation-based simulation method. [Internet] [Thesis]. Oregon Health Sciences University; 2013. [cited 2019 Nov 21]. Available from: doi:10.6083/M4BK19D8 ; http://digitalcommons.ohsu.edu/etd/957.

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

Council of Science Editors:

Beer JC. Power and sample size determination for time course microarray differential expression studies : a positive false discovery rate and permutation-based simulation method. [Thesis]. Oregon Health Sciences University; 2013. Available from: doi:10.6083/M4BK19D8 ; http://digitalcommons.ohsu.edu/etd/957

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


IUPUI

11. Whale, John W. Population genetic analysis of the black blow fly Phormia regina (Meigen) (Diptera: Calliphoridae).

Degree: 2015, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

The black blow fly, Phormia regina (Diptera: Calliphoridae), is a widely abundant fly autochthonous to North America. Like many other… (more)

Subjects/Keywords: Phormia regina  – Genome mapping  – Research; Blowflies  – Physiology  – Research  – North America; Blowflies  – Larvae  – Genetics  – Research; Life cycles (Biology)  – Genetic aspects; Molecular biology  – Mathematical models; Gene expression  – Statistical methods; Postmortem changes

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APA (6th Edition):

Whale, J. W. (2015). Population genetic analysis of the black blow fly Phormia regina (Meigen) (Diptera: Calliphoridae). (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/6722

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):

Whale, John W. “Population genetic analysis of the black blow fly Phormia regina (Meigen) (Diptera: Calliphoridae).” 2015. Thesis, IUPUI. Accessed November 21, 2019. http://hdl.handle.net/1805/6722.

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

MLA Handbook (7th Edition):

Whale, John W. “Population genetic analysis of the black blow fly Phormia regina (Meigen) (Diptera: Calliphoridae).” 2015. Web. 21 Nov 2019.

Vancouver:

Whale JW. Population genetic analysis of the black blow fly Phormia regina (Meigen) (Diptera: Calliphoridae). [Internet] [Thesis]. IUPUI; 2015. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/1805/6722.

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

Council of Science Editors:

Whale JW. Population genetic analysis of the black blow fly Phormia regina (Meigen) (Diptera: Calliphoridae). [Thesis]. IUPUI; 2015. Available from: http://hdl.handle.net/1805/6722

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


Victoria University of Wellington

12. Matti, Mukhlis. Exploring a Bioinformatics Clustering Algorithm.

Degree: 2004, Victoria University of Wellington

 This thesis explores and evaluates MAXCCLUS, a bioinformatics clustering algorithm, which was designed to be used to cluster genes from microarray experimental data. MAXCCLUS does… (more)

Subjects/Keywords: Bioinformatics; Cluster analysis; Gene expression; Statistical methods; Data mining; Algorithms

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APA (6th Edition):

Matti, M. (2004). Exploring a Bioinformatics Clustering Algorithm. (Masters Thesis). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/19

Chicago Manual of Style (16th Edition):

Matti, Mukhlis. “Exploring a Bioinformatics Clustering Algorithm.” 2004. Masters Thesis, Victoria University of Wellington. Accessed November 21, 2019. http://hdl.handle.net/10063/19.

MLA Handbook (7th Edition):

Matti, Mukhlis. “Exploring a Bioinformatics Clustering Algorithm.” 2004. Web. 21 Nov 2019.

Vancouver:

Matti M. Exploring a Bioinformatics Clustering Algorithm. [Internet] [Masters thesis]. Victoria University of Wellington; 2004. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/10063/19.

Council of Science Editors:

Matti M. Exploring a Bioinformatics Clustering Algorithm. [Masters Thesis]. Victoria University of Wellington; 2004. Available from: http://hdl.handle.net/10063/19


Michigan State University

13. Steibel, Juan Pedro. Improving experimental design and statistical inference for transcriptional profiling experiments.

Degree: PhD, Department of Animal Science, 2007, Michigan State University

Subjects/Keywords: Experimental design; Mathematical statistics; Genomics – Experiments – Design; DNA microarrays – Statistical methods; Gene expression – Statistical methods

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

APA (6th Edition):

Steibel, J. P. (2007). Improving experimental design and statistical inference for transcriptional profiling experiments. (Doctoral Dissertation). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:38414

Chicago Manual of Style (16th Edition):

Steibel, Juan Pedro. “Improving experimental design and statistical inference for transcriptional profiling experiments.” 2007. Doctoral Dissertation, Michigan State University. Accessed November 21, 2019. http://etd.lib.msu.edu/islandora/object/etd:38414.

MLA Handbook (7th Edition):

Steibel, Juan Pedro. “Improving experimental design and statistical inference for transcriptional profiling experiments.” 2007. Web. 21 Nov 2019.

Vancouver:

Steibel JP. Improving experimental design and statistical inference for transcriptional profiling experiments. [Internet] [Doctoral dissertation]. Michigan State University; 2007. [cited 2019 Nov 21]. Available from: http://etd.lib.msu.edu/islandora/object/etd:38414.

Council of Science Editors:

Steibel JP. Improving experimental design and statistical inference for transcriptional profiling experiments. [Doctoral Dissertation]. Michigan State University; 2007. Available from: http://etd.lib.msu.edu/islandora/object/etd:38414


University of Houston

14. Le, Yen H. 1984-. Shape Priors for Segmentation of Mouse Brain in Gene Expression Images.

Degree: Computer Science, Department of, 2014, University of Houston

 The quantification and comparison of gene expression data across images plays a key role in understanding the functional network of various genes. To enable studying… (more)

Subjects/Keywords: statistical shape model; PDM; ASM; PDM-ENLOR; gene expression images

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APA (6th Edition):

Le, Y. H. 1. (2014). Shape Priors for Segmentation of Mouse Brain in Gene Expression Images. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/1793

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):

Le, Yen H 1984-. “Shape Priors for Segmentation of Mouse Brain in Gene Expression Images.” 2014. Thesis, University of Houston. Accessed November 21, 2019. http://hdl.handle.net/10657/1793.

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

MLA Handbook (7th Edition):

Le, Yen H 1984-. “Shape Priors for Segmentation of Mouse Brain in Gene Expression Images.” 2014. Web. 21 Nov 2019.

Vancouver:

Le YH1. Shape Priors for Segmentation of Mouse Brain in Gene Expression Images. [Internet] [Thesis]. University of Houston; 2014. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/10657/1793.

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

Council of Science Editors:

Le YH1. Shape Priors for Segmentation of Mouse Brain in Gene Expression Images. [Thesis]. University of Houston; 2014. Available from: http://hdl.handle.net/10657/1793

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


University of Illinois – Urbana-Champaign

15. Chen, Chieh-Chun. Statistical mechanical modeling of eukaryotic gene regulation.

Degree: PhD, 0408, 2013, University of Illinois – Urbana-Champaign

Gene expression patterns are regulated by gene regulatory networks. Central to transcriptional regulation of gene expression is the regulation of the quantities of transcription factors… (more)

Subjects/Keywords: Statistical mechanics; transcriptional regulation; transcription factors; epignomes; gene expression

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APA (6th Edition):

Chen, C. (2013). Statistical mechanical modeling of eukaryotic gene regulation. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/42149

Chicago Manual of Style (16th Edition):

Chen, Chieh-Chun. “Statistical mechanical modeling of eukaryotic gene regulation.” 2013. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed November 21, 2019. http://hdl.handle.net/2142/42149.

MLA Handbook (7th Edition):

Chen, Chieh-Chun. “Statistical mechanical modeling of eukaryotic gene regulation.” 2013. Web. 21 Nov 2019.

Vancouver:

Chen C. Statistical mechanical modeling of eukaryotic gene regulation. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2013. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/2142/42149.

Council of Science Editors:

Chen C. Statistical mechanical modeling of eukaryotic gene regulation. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2013. Available from: http://hdl.handle.net/2142/42149


University of Southern California

16. Yan, Xiting. Statistical modeling of sequence and gene expression data to infer gene regulatory networks.

Degree: PhD, Molecular & Computational Biology, 2009, University of Southern California

 Understanding the gene regulatory network has always been one of the important and challenging tasks to understanding the mechanisms behind different biological processes or behaviors… (more)

Subjects/Keywords: sequence; gene expression; regulatory networks; data analysis; statistical modeling; inference

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

APA (6th Edition):

Yan, X. (2009). Statistical modeling of sequence and gene expression data to infer gene regulatory networks. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/175848/rec/6046

Chicago Manual of Style (16th Edition):

Yan, Xiting. “Statistical modeling of sequence and gene expression data to infer gene regulatory networks.” 2009. Doctoral Dissertation, University of Southern California. Accessed November 21, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/175848/rec/6046.

MLA Handbook (7th Edition):

Yan, Xiting. “Statistical modeling of sequence and gene expression data to infer gene regulatory networks.” 2009. Web. 21 Nov 2019.

Vancouver:

Yan X. Statistical modeling of sequence and gene expression data to infer gene regulatory networks. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2019 Nov 21]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/175848/rec/6046.

Council of Science Editors:

Yan X. Statistical modeling of sequence and gene expression data to infer gene regulatory networks. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/175848/rec/6046


IUPUI

17. Kilaru, Gokhul Krishna. USE OF APRIORI KNOWLEDGE ON DYNAMIC BAYESIAN MODELS IN TIME-COURSE EXPRESSION DATA PREDICTION.

Degree: 2012, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

Bayesian networks, one of the most widely used techniques to understand or predict the future by making use of current… (more)

Subjects/Keywords: BAYESIAN NETWORKS, GENE EXPRESSION, DYNAMIC BAYESIAN NETWORKS, HIDDEN MARKOV MODELS; Bayesian statistical decision theory; Gene expression

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APA (6th Edition):

Kilaru, G. K. (2012). USE OF APRIORI KNOWLEDGE ON DYNAMIC BAYESIAN MODELS IN TIME-COURSE EXPRESSION DATA PREDICTION. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/2774

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):

Kilaru, Gokhul Krishna. “USE OF APRIORI KNOWLEDGE ON DYNAMIC BAYESIAN MODELS IN TIME-COURSE EXPRESSION DATA PREDICTION.” 2012. Thesis, IUPUI. Accessed November 21, 2019. http://hdl.handle.net/1805/2774.

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

MLA Handbook (7th Edition):

Kilaru, Gokhul Krishna. “USE OF APRIORI KNOWLEDGE ON DYNAMIC BAYESIAN MODELS IN TIME-COURSE EXPRESSION DATA PREDICTION.” 2012. Web. 21 Nov 2019.

Vancouver:

Kilaru GK. USE OF APRIORI KNOWLEDGE ON DYNAMIC BAYESIAN MODELS IN TIME-COURSE EXPRESSION DATA PREDICTION. [Internet] [Thesis]. IUPUI; 2012. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/1805/2774.

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

Council of Science Editors:

Kilaru GK. USE OF APRIORI KNOWLEDGE ON DYNAMIC BAYESIAN MODELS IN TIME-COURSE EXPRESSION DATA PREDICTION. [Thesis]. IUPUI; 2012. Available from: http://hdl.handle.net/1805/2774

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


University of Hong Kong

18. Li, Miaoxin. Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications.

Degree: PhD, 2009, University of Hong Kong

published_or_final_version

Biochemistry

Doctoral

Doctor of Philosophy

Advisors/Committee Members: Sham, PC, Song, Y.

Subjects/Keywords: Gene mapping - Statistical methods.; Bioinformatics.

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APA (6th Edition):

Li, M. (2009). Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications. (Doctoral Dissertation). University of Hong Kong. Retrieved from Li, M. [李淼新]. (2009). Development of a bioinformatics and statistical framework to integrate biological resources for genome-wide genetic mapping and its applications. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4357203 ; http://dx.doi.org/10.5353/th_b4357203 ; http://hdl.handle.net/10722/56788

Chicago Manual of Style (16th Edition):

Li, Miaoxin. “Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications.” 2009. Doctoral Dissertation, University of Hong Kong. Accessed November 21, 2019. Li, M. [李淼新]. (2009). Development of a bioinformatics and statistical framework to integrate biological resources for genome-wide genetic mapping and its applications. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4357203 ; http://dx.doi.org/10.5353/th_b4357203 ; http://hdl.handle.net/10722/56788.

MLA Handbook (7th Edition):

Li, Miaoxin. “Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications.” 2009. Web. 21 Nov 2019.

Vancouver:

Li M. Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications. [Internet] [Doctoral dissertation]. University of Hong Kong; 2009. [cited 2019 Nov 21]. Available from: Li, M. [李淼新]. (2009). Development of a bioinformatics and statistical framework to integrate biological resources for genome-wide genetic mapping and its applications. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4357203 ; http://dx.doi.org/10.5353/th_b4357203 ; http://hdl.handle.net/10722/56788.

Council of Science Editors:

Li M. Development of a bioinformatics and statistical framework to integratebiological resources for genome-wide genetic mapping and itsapplications. [Doctoral Dissertation]. University of Hong Kong; 2009. Available from: Li, M. [李淼新]. (2009). Development of a bioinformatics and statistical framework to integrate biological resources for genome-wide genetic mapping and its applications. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4357203 ; http://dx.doi.org/10.5353/th_b4357203 ; http://hdl.handle.net/10722/56788


University of Hong Kong

19. Kwan, Sheung-him. Statistical methods and analyses in human gene mapping.

Degree: PhD, 2009, University of Hong Kong

published_or_final_version

Psychiatry

Doctoral

Doctor of Philosophy

Advisors/Committee Members: Sham, PC.

Subjects/Keywords: Human gene mapping - Statistical methods.

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

APA (6th Edition):

Kwan, S. (2009). Statistical methods and analyses in human gene mapping. (Doctoral Dissertation). University of Hong Kong. Retrieved from Kwan, S. [關尚謙]. (2009). Statistical methods and analyses in human gene mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4375911 ; http://dx.doi.org/10.5353/th_b4375911 ; http://hdl.handle.net/10722/57617

Chicago Manual of Style (16th Edition):

Kwan, Sheung-him. “Statistical methods and analyses in human gene mapping.” 2009. Doctoral Dissertation, University of Hong Kong. Accessed November 21, 2019. Kwan, S. [關尚謙]. (2009). Statistical methods and analyses in human gene mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4375911 ; http://dx.doi.org/10.5353/th_b4375911 ; http://hdl.handle.net/10722/57617.

MLA Handbook (7th Edition):

Kwan, Sheung-him. “Statistical methods and analyses in human gene mapping.” 2009. Web. 21 Nov 2019.

Vancouver:

Kwan S. Statistical methods and analyses in human gene mapping. [Internet] [Doctoral dissertation]. University of Hong Kong; 2009. [cited 2019 Nov 21]. Available from: Kwan, S. [關尚謙]. (2009). Statistical methods and analyses in human gene mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4375911 ; http://dx.doi.org/10.5353/th_b4375911 ; http://hdl.handle.net/10722/57617.

Council of Science Editors:

Kwan S. Statistical methods and analyses in human gene mapping. [Doctoral Dissertation]. University of Hong Kong; 2009. Available from: Kwan, S. [關尚謙]. (2009). Statistical methods and analyses in human gene mapping. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4375911 ; http://dx.doi.org/10.5353/th_b4375911 ; http://hdl.handle.net/10722/57617


University of Oxford

20. Antonyuk, Alexander. Statistical methodology for QTL mapping and genome-wide association studies.

Degree: PhD, 2009, University of Oxford

 This work deals with statistical tests of association between genetic markers and disease phenotypes. The main criterion used for comparing the tests is statistical power.… (more)

Subjects/Keywords: 572.8; Gene mapping – Statistical methods; Phenotype – Mathematical models

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APA (6th Edition):

Antonyuk, A. (2009). Statistical methodology for QTL mapping and genome-wide association studies. (Doctoral Dissertation). University of Oxford. Retrieved from https://ora.ox.ac.uk/objects/uuid:23393c76-b7ef-44c2-a06f-3b23e3a6d936 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670017

Chicago Manual of Style (16th Edition):

Antonyuk, Alexander. “Statistical methodology for QTL mapping and genome-wide association studies.” 2009. Doctoral Dissertation, University of Oxford. Accessed November 21, 2019. https://ora.ox.ac.uk/objects/uuid:23393c76-b7ef-44c2-a06f-3b23e3a6d936 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670017.

MLA Handbook (7th Edition):

Antonyuk, Alexander. “Statistical methodology for QTL mapping and genome-wide association studies.” 2009. Web. 21 Nov 2019.

Vancouver:

Antonyuk A. Statistical methodology for QTL mapping and genome-wide association studies. [Internet] [Doctoral dissertation]. University of Oxford; 2009. [cited 2019 Nov 21]. Available from: https://ora.ox.ac.uk/objects/uuid:23393c76-b7ef-44c2-a06f-3b23e3a6d936 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670017.

Council of Science Editors:

Antonyuk A. Statistical methodology for QTL mapping and genome-wide association studies. [Doctoral Dissertation]. University of Oxford; 2009. Available from: https://ora.ox.ac.uk/objects/uuid:23393c76-b7ef-44c2-a06f-3b23e3a6d936 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.670017


Michigan State University

21. Wei, Changshuai. Statistical methods for high-dimensional sequencing studies.

Degree: 2014, Michigan State University

Thesis Ph. D. Michigan State University. Epidemiology 2014.

Background: With the advance of next generation sequencing technology, a massive amount of sequencing data are generated… (more)

Subjects/Keywords: Biometry; Gene mapping – Statistical methods; Bioinformatics – Methodology; Biostatistics; Genetics; Bioinformatics

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APA (6th Edition):

Wei, C. (2014). Statistical methods for high-dimensional sequencing studies. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:3178

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):

Wei, Changshuai. “Statistical methods for high-dimensional sequencing studies.” 2014. Thesis, Michigan State University. Accessed November 21, 2019. http://etd.lib.msu.edu/islandora/object/etd:3178.

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

MLA Handbook (7th Edition):

Wei, Changshuai. “Statistical methods for high-dimensional sequencing studies.” 2014. Web. 21 Nov 2019.

Vancouver:

Wei C. Statistical methods for high-dimensional sequencing studies. [Internet] [Thesis]. Michigan State University; 2014. [cited 2019 Nov 21]. Available from: http://etd.lib.msu.edu/islandora/object/etd:3178.

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

Council of Science Editors:

Wei C. Statistical methods for high-dimensional sequencing studies. [Thesis]. Michigan State University; 2014. Available from: http://etd.lib.msu.edu/islandora/object/etd:3178

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


Michigan State University

22. Gao, Bin, Ph. D. Graph estimation and network constrained regularization with applications in genetical genomics analysis.

Degree: 2015, Michigan State University

Thesis Ph. D. Michigan State University. Statistics 2015

Estimation and application of graphical structure are important topics in modern statistics. Graphical structure is an ideal… (more)

Subjects/Keywords: Gene regulatory networks; Genomics – Statistical methods; Graphical modeling (Statistics); Statistics

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APA (6th Edition):

Gao, Bin, P. D. (2015). Graph estimation and network constrained regularization with applications in genetical genomics analysis. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:3745

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):

Gao, Bin, Ph D. “Graph estimation and network constrained regularization with applications in genetical genomics analysis.” 2015. Thesis, Michigan State University. Accessed November 21, 2019. http://etd.lib.msu.edu/islandora/object/etd:3745.

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

MLA Handbook (7th Edition):

Gao, Bin, Ph D. “Graph estimation and network constrained regularization with applications in genetical genomics analysis.” 2015. Web. 21 Nov 2019.

Vancouver:

Gao, Bin PD. Graph estimation and network constrained regularization with applications in genetical genomics analysis. [Internet] [Thesis]. Michigan State University; 2015. [cited 2019 Nov 21]. Available from: http://etd.lib.msu.edu/islandora/object/etd:3745.

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

Council of Science Editors:

Gao, Bin PD. Graph estimation and network constrained regularization with applications in genetical genomics analysis. [Thesis]. Michigan State University; 2015. Available from: http://etd.lib.msu.edu/islandora/object/etd:3745

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


University of Hong Kong

23. Liu, Lizhong. Development of tunable synthetic circuits for precise control of gene expression in mammalian cells.

Degree: PhD, 2016, University of Hong Kong

 Precise control of gene expression is not only crucial for the study of gene functions but also pivotal to the development of sophisticated synthetic gene(more)

Subjects/Keywords: Gene expression

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

APA (6th Edition):

Liu, L. (2016). Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. (Doctoral Dissertation). University of Hong Kong. Retrieved from Liu, L. [劉立中]. (2016). Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5816250. ; http://dx.doi.org/10.5353/th_b5816250 ; http://hdl.handle.net/10722/248965

Chicago Manual of Style (16th Edition):

Liu, Lizhong. “Development of tunable synthetic circuits for precise control of gene expression in mammalian cells.” 2016. Doctoral Dissertation, University of Hong Kong. Accessed November 21, 2019. Liu, L. [劉立中]. (2016). Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5816250. ; http://dx.doi.org/10.5353/th_b5816250 ; http://hdl.handle.net/10722/248965.

MLA Handbook (7th Edition):

Liu, Lizhong. “Development of tunable synthetic circuits for precise control of gene expression in mammalian cells.” 2016. Web. 21 Nov 2019.

Vancouver:

Liu L. Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. [Internet] [Doctoral dissertation]. University of Hong Kong; 2016. [cited 2019 Nov 21]. Available from: Liu, L. [劉立中]. (2016). Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5816250. ; http://dx.doi.org/10.5353/th_b5816250 ; http://hdl.handle.net/10722/248965.

Council of Science Editors:

Liu L. Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. [Doctoral Dissertation]. University of Hong Kong; 2016. Available from: Liu, L. [劉立中]. (2016). Development of tunable synthetic circuits for precise control of gene expression in mammalian cells. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5816250. ; http://dx.doi.org/10.5353/th_b5816250 ; http://hdl.handle.net/10722/248965


University of Hong Kong

24. Wang, Yan. Bioinformatics analysis of genetic and epigenetic factors regulating gene expression.

Degree: PhD, 2015, University of Hong Kong

Gene transcription is a fundamental and important step for cellular function, biological process and pathogenesis. The diversified temporal and spatial patterns of gene expression are… (more)

Subjects/Keywords: Gene expression

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

APA (6th Edition):

Wang, Y. (2015). Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. (Doctoral Dissertation). University of Hong Kong. Retrieved from Wang, Y. [王嫣]. (2015). Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5387960 ; http://dx.doi.org/10.5353/th_b5387960 ; http://hdl.handle.net/10722/222277

Chicago Manual of Style (16th Edition):

Wang, Yan. “Bioinformatics analysis of genetic and epigenetic factors regulating gene expression.” 2015. Doctoral Dissertation, University of Hong Kong. Accessed November 21, 2019. Wang, Y. [王嫣]. (2015). Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5387960 ; http://dx.doi.org/10.5353/th_b5387960 ; http://hdl.handle.net/10722/222277.

MLA Handbook (7th Edition):

Wang, Yan. “Bioinformatics analysis of genetic and epigenetic factors regulating gene expression.” 2015. Web. 21 Nov 2019.

Vancouver:

Wang Y. Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. [Internet] [Doctoral dissertation]. University of Hong Kong; 2015. [cited 2019 Nov 21]. Available from: Wang, Y. [王嫣]. (2015). Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5387960 ; http://dx.doi.org/10.5353/th_b5387960 ; http://hdl.handle.net/10722/222277.

Council of Science Editors:

Wang Y. Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. [Doctoral Dissertation]. University of Hong Kong; 2015. Available from: Wang, Y. [王嫣]. (2015). Bioinformatics analysis of genetic and epigenetic factors regulating gene expression. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5387960 ; http://dx.doi.org/10.5353/th_b5387960 ; http://hdl.handle.net/10722/222277


University of Hong Kong

25. He, Feng. Detection of parent-of-origin effects and association in relation to aquantitative trait.

Degree: M. Phil., 2010, University of Hong Kong

published_or_final_version

Statistics and Actuarial Science

Master

Master of Philosophy

Advisors/Committee Members: Fung, TWK.

Subjects/Keywords: Gene mapping - Statistical methods.; Genomic imprinting - Statistical methods.

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APA (6th Edition):

He, F. (2010). Detection of parent-of-origin effects and association in relation to aquantitative trait. (Masters Thesis). University of Hong Kong. Retrieved from He, F. [贺峰]. (2010). Detection of parent-of-origin effects and association in relation to a quantitative trait. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4492140 ; http://dx.doi.org/10.5353/th_b4492140 ; http://hdl.handle.net/10722/141901

Chicago Manual of Style (16th Edition):

He, Feng. “Detection of parent-of-origin effects and association in relation to aquantitative trait.” 2010. Masters Thesis, University of Hong Kong. Accessed November 21, 2019. He, F. [贺峰]. (2010). Detection of parent-of-origin effects and association in relation to a quantitative trait. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4492140 ; http://dx.doi.org/10.5353/th_b4492140 ; http://hdl.handle.net/10722/141901.

MLA Handbook (7th Edition):

He, Feng. “Detection of parent-of-origin effects and association in relation to aquantitative trait.” 2010. Web. 21 Nov 2019.

Vancouver:

He F. Detection of parent-of-origin effects and association in relation to aquantitative trait. [Internet] [Masters thesis]. University of Hong Kong; 2010. [cited 2019 Nov 21]. Available from: He, F. [贺峰]. (2010). Detection of parent-of-origin effects and association in relation to a quantitative trait. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4492140 ; http://dx.doi.org/10.5353/th_b4492140 ; http://hdl.handle.net/10722/141901.

Council of Science Editors:

He F. Detection of parent-of-origin effects and association in relation to aquantitative trait. [Masters Thesis]. University of Hong Kong; 2010. Available from: He, F. [贺峰]. (2010). Detection of parent-of-origin effects and association in relation to a quantitative trait. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b4492140 ; http://dx.doi.org/10.5353/th_b4492140 ; http://hdl.handle.net/10722/141901


The Ohio State University

26. Iyer Biswas, Srividya. Applications of Methods of Non-equilibrium Statistical Physics to Models of Stochastic Gene Expression.

Degree: PhD, Physics, 2009, The Ohio State University

  In this dissertation I study the role of stochastic fluctuations in numbers of key biochemical molecules in implementing the regulation of gene expression, the… (more)

Subjects/Keywords: Physics; non equilibrium; statistical physics; stochastic gene expression; protein distributions; mRNA distributions

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APA (6th Edition):

Iyer Biswas, S. (2009). Applications of Methods of Non-equilibrium Statistical Physics to Models of Stochastic Gene Expression. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1248731428

Chicago Manual of Style (16th Edition):

Iyer Biswas, Srividya. “Applications of Methods of Non-equilibrium Statistical Physics to Models of Stochastic Gene Expression.” 2009. Doctoral Dissertation, The Ohio State University. Accessed November 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1248731428.

MLA Handbook (7th Edition):

Iyer Biswas, Srividya. “Applications of Methods of Non-equilibrium Statistical Physics to Models of Stochastic Gene Expression.” 2009. Web. 21 Nov 2019.

Vancouver:

Iyer Biswas S. Applications of Methods of Non-equilibrium Statistical Physics to Models of Stochastic Gene Expression. [Internet] [Doctoral dissertation]. The Ohio State University; 2009. [cited 2019 Nov 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1248731428.

Council of Science Editors:

Iyer Biswas S. Applications of Methods of Non-equilibrium Statistical Physics to Models of Stochastic Gene Expression. [Doctoral Dissertation]. The Ohio State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1248731428


University of Missouri – Columbia

27. Cui, Shiqi. Bayesian analysis for detecting differentially expressed genes from RNA-seq data.

Degree: 2014, University of Missouri – Columbia

 [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces hmmSeq, a model-based hierarchical Bayesian technique for detecting differentially expressed genes from… (more)

Subjects/Keywords: Hidden Markov models; Bayesian statistical decision theory; Gene expression  – Research; Nucleotide sequence

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APA (6th Edition):

Cui, S. (2014). Bayesian analysis for detecting differentially expressed genes from RNA-seq data. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/48204

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):

Cui, Shiqi. “Bayesian analysis for detecting differentially expressed genes from RNA-seq data.” 2014. Thesis, University of Missouri – Columbia. Accessed November 21, 2019. http://hdl.handle.net/10355/48204.

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

MLA Handbook (7th Edition):

Cui, Shiqi. “Bayesian analysis for detecting differentially expressed genes from RNA-seq data.” 2014. Web. 21 Nov 2019.

Vancouver:

Cui S. Bayesian analysis for detecting differentially expressed genes from RNA-seq data. [Internet] [Thesis]. University of Missouri – Columbia; 2014. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/10355/48204.

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

Council of Science Editors:

Cui S. Bayesian analysis for detecting differentially expressed genes from RNA-seq data. [Thesis]. University of Missouri – Columbia; 2014. Available from: http://hdl.handle.net/10355/48204

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


The Ohio State University

28. Wang, Tao. Statistical design and analysis of microarray experiments.

Degree: PhD, Statistics, 2005, The Ohio State University

 Microarray, a bio-technology that allows monitoring of gene expressions for thousands of genes simultaneously, has revolutionized biological and genomic research and holds promising potentials in… (more)

Subjects/Keywords: Statistics; microarray; gene expression; statistical analysis; modeling; statistical design

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APA (6th Edition):

Wang, T. (2005). Statistical design and analysis of microarray experiments. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363

Chicago Manual of Style (16th Edition):

Wang, Tao. “Statistical design and analysis of microarray experiments.” 2005. Doctoral Dissertation, The Ohio State University. Accessed November 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363.

MLA Handbook (7th Edition):

Wang, Tao. “Statistical design and analysis of microarray experiments.” 2005. Web. 21 Nov 2019.

Vancouver:

Wang T. Statistical design and analysis of microarray experiments. [Internet] [Doctoral dissertation]. The Ohio State University; 2005. [cited 2019 Nov 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363.

Council of Science Editors:

Wang T. Statistical design and analysis of microarray experiments. [Doctoral Dissertation]. The Ohio State University; 2005. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363


University of Florida

29. Bacher, Rhonda. RNA-seq data: normal models and missing data.

Degree: 2012, University of Florida

 RNA-Seq is a tool used for assessing gene expression based on read counts from high throughput sequencing. Many analysis methods to detect differential expression thus… (more)

Subjects/Keywords: Data imputation; Datasets; Missing data; Modeling; RNA; Sequencing; Sorghum; Statistical discrepancies; Statistical models; Statistics; Gene expression; Messenger RNA

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

APA (6th Edition):

Bacher, R. (2012). RNA-seq data: normal models and missing data. (Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00060616

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):

Bacher, Rhonda. “RNA-seq data: normal models and missing data.” 2012. Thesis, University of Florida. Accessed November 21, 2019. http://ufdc.ufl.edu/AA00060616.

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

MLA Handbook (7th Edition):

Bacher, Rhonda. “RNA-seq data: normal models and missing data.” 2012. Web. 21 Nov 2019.

Vancouver:

Bacher R. RNA-seq data: normal models and missing data. [Internet] [Thesis]. University of Florida; 2012. [cited 2019 Nov 21]. Available from: http://ufdc.ufl.edu/AA00060616.

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

Council of Science Editors:

Bacher R. RNA-seq data: normal models and missing data. [Thesis]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/AA00060616

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


Universitat Politècnica de València

30. Tarazona Campos, Sonia. Statistical methods for transcriptomics: From microarrays to RNA-seq .

Degree: 2015, Universitat Politècnica de València

 La transcriptómica estudia el nivel de expresión de los genes en distintas condiciones experimentales para tratar de identificar los genes asociados a un fenotipo dado… (more)

Subjects/Keywords: Bioestadistics; Bioinformatics, Variable selection; Non-parametric statistical methods; Differential expression; Microarrays; RNA-seq; Transcriptomics

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

APA (6th Edition):

Tarazona Campos, S. (2015). Statistical methods for transcriptomics: From microarrays to RNA-seq . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/48485

Chicago Manual of Style (16th Edition):

Tarazona Campos, Sonia. “Statistical methods for transcriptomics: From microarrays to RNA-seq .” 2015. Doctoral Dissertation, Universitat Politècnica de València. Accessed November 21, 2019. http://hdl.handle.net/10251/48485.

MLA Handbook (7th Edition):

Tarazona Campos, Sonia. “Statistical methods for transcriptomics: From microarrays to RNA-seq .” 2015. Web. 21 Nov 2019.

Vancouver:

Tarazona Campos S. Statistical methods for transcriptomics: From microarrays to RNA-seq . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2015. [cited 2019 Nov 21]. Available from: http://hdl.handle.net/10251/48485.

Council of Science Editors:

Tarazona Campos S. Statistical methods for transcriptomics: From microarrays to RNA-seq . [Doctoral Dissertation]. Universitat Politècnica de València; 2015. Available from: http://hdl.handle.net/10251/48485

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